About Us We're a U.S.-based B2B technology services company (low-voltage / network infrastructure integrator — Wi-Fi, structured cabling, AV, DAS, managed services). We're scaling and need to formalize our sales commission system in HubSpot Enterprise. Important: The architecture is already fully designed. We have a 40-page developer-grade build specification (v3.1) ready to hand off after contract signing + NDA. You're executing against a spec, not designing one. If you prefer greenfield architecture work, this isn't the right gig. What's Being Built A three-object commission tracking system: 1. Deal (existing) — sales-side commission setup at quote stage 2. Project (existing) — execution-side tracking 3. Commission Record (new custom object) — individual commission events with associations to both Deal and Project Concrete Scope - ~48 new properties across the three objects (15 on Deal, ~33 on Project, 21 on the new Commission Record object) - 8 new HubSpot workflows (1 existing workflow stays untouched — you'll extend, not modify) - 5 calculated properties with specific formulas defined in the spec - A bidirectional sync pattern (Project execution data mirrors back to Deal as read-only fields) - 16 reports across 4 role-based dashboards (Sales Rep, Finance/Owner, Quote Accuracy, Sales Engineer) - 7 written test scenarios with expected outcomes Workflows Include - Lock commission baseline at Closed-Won (Deal → Project sync) - Mirror-back execution data (Project → Deal) - Commission Record creation at invoice events (with native Deal Splits handling — Operations Hub Custom Code required) - Variance check + branching at final invoice - Quote Review resolution (4 outcome branches) - Scheduled annual ARR renewal workflow - SE technical close spiff workflow - Clawback workflow for unpaid invoices Must-Have Experience - HubSpot Enterprise — Sales Hub + Operations Hub. Do not apply if you have not worked in Enterprise tier with custom objects. - Custom Object creation and configuration — properties, associations (primary/secondary), pipelines, field-level permissions - HubSpot Workflows with branching logic, scheduled triggers, multi-object enrollment, re-enrollment configuration - Operations Hub Custom Code Actions (JavaScript) — needed to iterate native Deal Splits and create N commission records per split. This is non-negotiable. - HubSpot Calculated Properties including handling nested conditional logic limitations - HubSpot Reports & Dashboards — custom report builder, multi-object reports - Native HubSpot Deal Splits feature Nice-to-Have - QuickBooks Online + HubSpot integration experience (Phase 2 work, August 2026 — separate contract if mutual fit) - Sales operations or commission accounting domain knowledge - B2B services industry context What We Provide - Full 40-page build specification post-contract (covers property inventory, workflow specs with triggers/filters/actions/branches, pipeline-specific logic for 5 delivery pipelines, calculated property formulas, 7 test scenarios, phased implementation sequence) - Existing foundation: 21 commission-related Deal properties already built and validated - Super Admin HubSpot access for the build - Direct access to operator (single decision-maker, no committee) — questions answered within 24 hours - Pre-validated technical decisions on 8 open architecture items Communication Expectations - Daily async standup (teams or email — your preference) - Weekly 30-minute video demo to operator - Architectural questions logged in shared doc

Senior Python Dev to Productionize a PPTX Medical Report Automation Prototype Overview We are a medical imaging report provider (Brain & Spine Injury Imaging Experts). We have a working Python prototype that auto-populates branded PowerPoint (.pptx) medical report templates and exports them to PDF. We need a senior developer to productionize it into a reliable, deterministic, well-documented tool. This is an automation/scripting engagement, not a slide-design job. What you'll build Harden and refactor our existing Python + python-pptx prototype into production-quality code. Fill locked-layout PowerPoint templates from structured input data (JSON) — text fields, findings lists, figure captions, measurements, and image placement. Generate required charts programmatically (e.g., NeuroQuant regional-percentile bar chart) rather than pasting static images. Export pixel-consistent PDFs (Aspose.Slides acceptable) that render identically on every run. Build a validation script that checks each generated report against required rules (footer text, page count, required fields, figure/label integrity) and flags deviations. Adapt the same engine to a second report type (Thoracic Spine) after the primary TBI report is accepted. Determinism requirement The tool must produce byte-for-byte consistent output across runs on the same input — same fonts, same layout, same positioning. Please describe in your proposal how you guarantee deterministic rendering and handle font embedding/substitution. Known Sample Drift — Footer Must Be Corrected The attached sample reports contain intentional footer inconsistencies that must NOT be reproduced. The signature-block footer currently varies across pages (some pages show only "Board Certified Radiologist," others add "Fellowship Trained in Musculoskeletal Imaging"). This drift is a known defect in the samples. The AUTHORITATIVE footer is the version we will supply in the spec sheet, and it must be applied identically on every page of every report. Your validation script must detect and reject any page whose footer does not exactly match the approved footer text. Do not treat the samples as the source of truth for footer content — treat the supplied spec as authoritative. Compliance / data handling This project involves medical reports. All development and testing will use de-identified sample data and dummy files only; you will not receive real patient PHI. A mutual NDA is required before we share the prototype code, templates, or licenses. Final report delivery to our HIPAA-compliant ShareFile account is handled with sandbox/test credentials during development; production keys are connected by us. Optional Phase 6 — Automated ShareFile Delivery Add a step that uploads the final PDF to a specified folder in our HIPAA-compliant ShareFile (Citrix) account via the ShareFile REST API, using a configurable case-to-folder mapping. Build/test with a non-PHI test folder and scoped test credentials; production credentials supplied and connected by client. Include setup instructions. Milestones (fixed price, ~$5,000 total, negotiable) Paid proof-of-concept: regenerate one approved sample report from our prototype on your environment, matching our reference output (small milestone — go/no-go gate). Production refactor of the fill engine and template handling. Deterministic PDF export + font handling. NeuroQuant chart generation + figure/label integrity. Validation script (footer, page count, required fields, drift detection). Spine report adaptation. (Optional Phase 6: ShareFile delivery.) A completion bonus applies for full delivery within 10 days of the awarded start. Required skills Python, python-pptx, Aspose, Microsoft PowerPoint, automation, data visualization, JSON data handling. API integration (ShareFile REST) a plus. To apply, please answer: Have you built PowerPoint/PPTX automation with python-pptx and/or Aspose? Share an example. How do you guarantee deterministic, pixel-consistent PDF output (fonts, layout)? Have you integrated the ShareFile (Citrix) API or similar OAuth-based file-storage APIs? Estimated timeline to complete Milestones 1–5. Attachments: De-identified sample reports (TBI and Spine) are attached for reference. Prototype code, real case data, and Aspose licenses will be provided after the NDA is signed.

Commercial Architect wanted for a variety of projects. First, we are needing a "Door Schedule" for a completed set of plans. A simple JPG of the schedule will suffice, which we can add to a page. No stamp needed, just a resourceful and experienced commercial architect that is responsive, great with IBC codes, can address redlines quickly. Potential for frequent work and consistent projects. Thank you!

DESCRIPTION; I'm building a data infrastructure product for ontology-driven AI context: object types, properties, and relationships materialized ahead of query time, so AI systems retrieve connected context fast instead of rebuilding it from raw sources on every request. I need experienced eyes on the ingestion foundation before anything gets built on top of it. The deliverables are fixed (below); hours are flexible — propose what you think the work honestly takes. Rate: my budget is $50–75/hr. That's a hard ceiling — proposals above that range can't be afforded and won't be considered, regardless of quality __________________________________________________________________________ WHO SHOULD APPLY A data engineer / data infrastructure engineer who understands what an ontology and a knowledge graph are and why they matter for AI systems — connected entities and relationships as first-class context, not just tables. You don't need graph database experience; you need to get why pre-materialized, relationship-aware data beats rebuilding context from raw sources on every query. If that framing clicks for you, you're the right kind of applicant. __________________________________________________________________________ THE PRODUCT, HIGH LEVEL: The platform deploys on a client's own infrastructure — we never see their data. Clients connect their data sources, define an ontology (object types, properties, relationships), and the platform materializes it across tiered storage. Later phases add a binary serve layer, SSD/RAM caching, and GPU-parallel query execution so AI systems and data applications retrieve connected context at very low latency. Target customers: companies running AI on complex connected data (security operations, healthcare, financial services) where privacy demands private deployment and speed matters. Storage note: the current prototype uses Iceberg on GCS for development convenience, but the architecture is intentionally built for any S3-compatible storage (on-prem S3, private cloud VPC, MinIO, etc.). Portability is a design requirement, not an afterthought — the platform must never be tied to a single cloud provider. __________________________________________________________________________ WHAT EXISTS TODAY: A working Python prototype: FastAPI, PyIceberg, PyArrow, Postgres, Supabase (metadata + sync ledger), GCS as the Iceberg warehouse. Architecture and design docs are provided for orientation. The cold path is functional and tested: a 31-test production suite ran against live infrastructure at 1M–5M row scale — core correctness, concurrency, failure injection (kill mid-sync, storage outages, lease expiry), idempotency/replay, rollback, a 50-sync soak, and audit checks. All passing, with a written sign-off document you'll receive. That's exactly why I'm hiring you: tests confirm behavior I anticipated. You're here for what I didn't anticipate — structural weaknesses, hidden risks, and edge cases that a test suite written by the same mind that wrote the pipeline can't catch. I'm strong on product and systems design, not low-level data engineering. The codebase is AI-assisted, and I want a professional to find what that typically accumulates. This is a prototype built from the ground up — no live client today. The goal: ensure the ingestion foundation is genuinely solid (data coming in from source correctly, at scale, repeatedly) so a scoped MVP pilot and beta release won't break under real usage. You are validating the foundation before anything gets built on top. __________________________________________________________________________ YOUR SCOPE — THE COLD PATH, END TO END Data source → validation → identity merge → materialized ontology in Iceberg on S3-compatible storage. The data connectors are in scope — they ARE Milestone 1. The platform supports exactly three ways data comes in, and your job includes confirming each one is genuinely production-grade, not just demo-grade: Postgres — full refresh and incremental watermark sync S3-compatible object storage (CSV) — currently GCS via S3 interop, but must work against any S3-compatible store (on-prem, MinIO, private VPC) Manual CSV upload — primarily for testing/onboarding For each connector, production-grade means: real error handling (bad credentials, unreachable source, permission failures, malformed/garbage data, schema drift), clear failure messages that tell a user what broke, no silent partial ingests, and sane retry/recovery behavior. If a connector swallows errors, loses rows quietly, or fails confusingly — that's exactly the finding I'm paying for. No other connectors are planned for this milestone. Three connectors that work correctly under stress beats ten that mostly work. Focus areas across the pipeline: Connectors — production-readiness and error handling as described above Identity & matching — entities staying consistent across syncs (PK merge, fingerprint mode, composite keys) Sync semantics — full refresh vs incremental watermark sync, replay idempotency, delete behavior Relationships — FK→PK edge materialization, rebuild triggers, orphan handling, stable node identity Versioning & audit — Iceberg snapshots, rollback, schema change lineage, sync ledger completeness Reliability — failure modes, partial writes, lock/lease behavior, silent wrong-data risks Code structure — dead code, duplication, coupling, fragility; source-specific logic must stay contained in each connector and never leak into the shared pipeline Explicitly out of scope: GPU execution, query kernels, binary serve formats, caching layers, query-time serving, and any new connector types — all future phases. Your scope ends at correct, versioned, audited data in Iceberg. __________________________________________________________________________ DELIVERABLES (in priority order) Prioritized written assessment — what's pilot-ready as-is, what must be fixed before a real pilot customer (with specific recommendations), and what the existing test suite missed (edge cases, risks, gaps). Active code changes — implement fixes for the highest-priority issues you find, directly in the repo. You'll have full repo access. I'm open to architecture changes and refinements as long as they're clearly explained with reasoning. A change log that teaches — for every change: what you changed, why it mattered, what it fixes or prevents, and what to watch for going forward. This isn't paperwork — I'm making a local engineering hire for the next milestone, and your write-ups become the onboarding record. Everyone who touches this codebase after you should learn from what you found. Fixes go deepest-risk-first. What you get from me: repo access, architecture/design docs, the test suite + sign-off report, and async availability for questions. __________________________________________________________________________ ***REQUIRED EXPERIENCE: 1)Production Python data pipelines 2)Apache Iceberg, Delta Lake, or Hudi (or strong Parquet/data-lake work) 3)Postgres 4)Merge/upsert, idempotency, watermark/CDC patterns Building or hardening data connectors that real users depend on************* __________________________________________________________________________ WHERE THIS CAN GO: This starts as a fixed-scope review. Separately, I plan to make my first part-time/full-time engineering hire locally (Dallas) to build Milestone 2 and beyond — SSD caching, serve layers, containerization, and microservices as the platform scales. For the right freelancer, there's opportunity to stay engaged on recurring scoped work — reviewing the foundation as it evolves and working in conjunction with that future hire. Not required, not promised — but the door is open if the work is strong. __________________________________________________________________________ *********HOW TO APPLY — READ CAREFULLY***** Answer this one question in your proposal, briefly and in your own words: "You're building a pipeline that ingests from Postgres and S3-compatible storage and materializes a connected ontology (entities + relationships) into Iceberg. How do you design the sync process to be reliable and idempotent — especially around watermarking, commits, and failure handling between steps?" Include your proposed hour estimate for the deliverables above. Get creative — attachments and notes welcome. Note on AI-generated proposals: I use AI heavily myself — but if your proposal or screening answer is clearly AI-generated boilerplate, you will be automatically rejected without consideration. I'm hiring your judgment and experience, not your ability to paste a prompt. Short, direct, human answers. __________________________________________________________________________ A NOTE ON TECHNOLOGY BOUNDARIES: ***QUICK EXAMPLE*** FastAPI and Iceberg are what the platform uses today, not permanent decisions. As the product scales, we may want to run FastAPI alongside a second framework, replace it entirely, or eventually move away from Iceberg toward a custom storage format optimized for the GPU serve layer. Those should be engineering decisions made on merit, not decisions we're forced into because the current code makes swapping painful. What I need confirmed: is the codebase modular enough that a change like that stays contained? Core business logic (validate, merge, materialize, version) should never be tangled directly with infrastructure. API routes should be thin entry points that hand off to service logic, not where business logic lives. Iceberg writes should be isolated behind a single abstraction. If those boundaries are clean, replacing or extending a technology layer is a focused engineering effort. If they're not, it touches everything and becomes a mess under deadline pressure with a full team. Flag anywhere that boundary is broken. That's a priority finding. __________________________________________________________________________ FINAL REMARKS: NDA & IP protections This engagement requires signing an NDA and IP assignments agreement before work begins; standard protections given you'll have full repo access to a pre-launch product. Documents are provided on day one; nothing unusual in them. If that's a dealbreaker, please don't apply.

I am seeking an experienced Automation / Embedded Systems Engineer to develop a robust, custom, production-ready Linux operating system image for a Raspberry Pi 3B+. The goal of this project is to create a 100% open-source, license-free "Gold Master" image that mimics a Unitronics smart relay/PLC workflow. This image will eventually be cloned across hundreds of offline poultry houses across a large-scale agricultural infrastructure. 🛠️ Hardware Stack (Target Environment) Controller: Raspberry Pi 3B+ booted completely offline (no internet access). Shield Stack: Sequent Microsystems Building Automation HAT + Sequent Stackable Smart UPS HAT (communicating via I2C). Display: Industrial HDMI Touchscreen. Power: 220V AC input stepped down via DIN-rail Mean Well power supplies (24V DC feeding the UPS HAT, separate line feeding the HDMI monitor). Outputs: On-board pilot relays triggering heavy-duty 220V AC industrial contactors/SSRs for high-voltage motors, heating, and lighting. 📋 Software & System Requirements Zero-Licensing Architecture: The entire system must utilize an open-source automation stack. We are using OpenPLC for the IEC 61131-3 visual ladder logic execution engine and Node-RED for the drag-and-drop HMI user interface. OS Hardening & Kiosk Mode: Built on Raspberry Pi OS Lite. The system must boot directly into a full-screen, fullscreen Chromium --kiosk browser pointing to the local Node-RED dashboard interface. There must be zero access to the underlying Linux terminal or desktop for farm operators. Display Power Management (DPMS): The system must utilize Linux screen blanking. The touchscreen backlight must completely power down after 5 minutes of inactivity and wake instantly back to the active HMI screen upon a physical touch event. Hardware Timekeeping (Offline): Synchronize the Linux system clock seamlessly on boot from the Sequent board’s battery-backed DS3231 Hardware RTC chip (hwclock) so the system maintains absolute real-world time accuracy without internet connectivity. Power Fail Resiliency & Retentive State: The software must listen to the Sequent UPS HAT. Upon 220V main power drop, a script must cleanly save current timer registers to retentive storage, write an event log, and execute a safe Linux shutdown to prevent SD card corruption. On power restoration, it must read the file and resume the cycle state seamlessly. HMI Password Protection: Implement a supervisor password/PIN keypad screen on the Node-RED interface, preventing unauthorized workers from modifying the timer settings. Data Logging & Audit Trail: Program local data logging (CSV or SQLite) to the SD card. It must record boot events, power losses, user logins, relay actions (start/stop), and track old vs. new values when configurations are edited. File writes must be buffered to optimize RAM and minimize SD card wear. Mass Replication Design: The image must be completely abstracted. All local variables (e.g., unique House ID, specific timer intervals) must be read from a local config file. Supervisors must be able to change these local configurations via the password-protected HMI screen so that the exact same master .img can be flashed onto hundreds of identical devices without code changes. 📦 Required Deliverables A single, universal flashable .img file ready to be duplicated onto standard SD cards. Clean, well-documented source code files for the OpenPLC logic and Node-RED flows. A highly clear, visual electrical wiring schematic showing exactly how the Pi, the Sequent HAT stack, the Mean Well power supplies, and the 220V contactors interconnect safely.

Job Title: Marketing Content Creator & Social Media Manager – B2B SaaS (Long-Term, Part-Time → Full-Time) Job Type: Ongoing / Contract Location: United States only (required) Hours: 30 hrs/week to start, with a clear path to 40 hrs Rate: $28–$35/hr (based on experience) About Gifted Gifted (gifted.co) is a B2B employee recognition and corporate gifting platform helping companies build cultures of appreciation. We're a lean, fast-moving team — and we need a sharp content creator to own our voice across every channel. This is a long-term role. We're not looking for a one-off project freelancer. We want someone who grows with us. What You'll Own Copywriting Social posts, email outreach, landing pages, ads, blog posts, and product messaging. You adapt tone by channel while keeping a consistent brand voice. Copy ships on time and drives real engagement. Social Media Management Day-to-day social across major platforms — content calendars, scheduling, community engagement, trend monitoring, and performance reporting. Consistent cadence and growing engagement are the benchmarks. AI-Assisted Production You're fluent in AI writing and image tools and use them to move faster without sacrificing quality. You build repeatable workflows and test variations. Bonus if you can build lightweight internal tools (AI coding experience is a genuine plus here). Design Execution You work inside existing Figma templates and must be able to create new on-brand assets — newsletters, pop-ups, one-pagers, and use case pages. Design background not required but is a plus! What's NOT Your Job Paid media budget or ad buying strategy You're a Fit If You Have: 2+ years creating content for a B2B SaaS or tech brand A portfolio with real copy, social, and/or Figma samples Hands-on AI tool experience (Claude, ChatGPT, Midjourney, Higgsfield, etc.) Strong written English — no fluff, no filler Reliable communication and the ability to manage your own workload Based in the United States (required — no exceptions) To Apply: 2–3 sentences on why this role fits you specifically 2–3 portfolio samples (copy, social, or design assets) The AI tools you use and how they show up in your workflow Your availability and hourly rate Applications without portfolio samples will not be reviewed.

Please start your proposal with the word “TRAINING” so I can narrow down the real applicants from AI responses. I am developing a web-based software training simulator for a widely manufactured physical product used across multiple industries. The product category has several competing manufacturers, each producing their own version with established menu structures, screen displays, button sequences, and user interface conventions. My simulator uses custom designs of product cases while replicating other products' user interfaces for training purposes. Before taking this product to market, I am seeking a practical, experience-based opinion of the following issue: I am seeking your assessment of the likelihood that a web-based commercial training product which replicates the menu structure, navigation flow, button sequences, screen layouts, and on-screen text of a real commercial device (while using entirely original artwork and excluding all manufacturer branding, logos, firmware, and proprietary code) would likely give rise to viable claims under U.S. intellectual property law, including copyright, trade dress, trademark, or related unfair competition theories. I understand the basics of Scènes à Faire, the Functionality Doctrine, the Idea-Expression Dichotomy, and Trade Dress (distinctiveness vs. likelihood of confusion). I'd like your opinion on whether these doctrines protect my approach and where any genuine risk sits. Deliverables: - Review of a brief project description and representative screenshots/mockups of the proposed simulator. - One 20-30 minute Zoom consultation to discuss the concept and clarify key facts. - A brief written summary (1–3 pages) outlining: Key intellectual property risks (if any); Your assessment of whether the proposed product is likely to present significant concerns under copyright, trade dress, trademark, or related unfair competition law; Practical recommendations to reduce legal exposure while preserving training functionality This is intended as a practical, experience-based assessment rather than a formal legal opinion letter or comprehensive legal research memorandum and no trademark, copyright, or patent clearance searches are required as part of this engagement. Confidentiality: Detailed product information and visual comparisons will be shared after engagement begins. Confidentiality will be governed by an NDA or the attorney’s professional obligations, as applicable. Ideal Experience: - Software and technology IP - User interface copyright issues - Trade dress and trademark analysis - Familiarity with functionality doctrine and scènes à faire principles Budget: $300 fixed price

We’re looking for an experienced full-stack React / React Native developer to help maintain and grow our B2B SaaS platform. Yelli is a web and mobile platform used by restaurants and hospitality businesses for training, onboarding, communication, testing, and operational documentation. The platform is already live with paying customers, and we are currently focused on improving the product, shipping new features, and scaling the platform. This is not a greenfield project. You'll be stepping into an existing codebase and working directly with the founder to improve, maintain, and evolve the product. Tech Stack: - Node.js - TypeScript - React - React Native - MySQL - AWS (EC2, S3, CodeDeploy) - Firebase - GitLab CI/CD What You'll Be Doing: - Maintaining and improving an existing web and mobile application - Fixing bugs and troubleshooting production issues - Shipping new features and enhancements - Reviewing existing architecture and suggesting improvements - Participating in weekly planning and progress meetings - Communicating progress and blockers proactively - Taking ownership of assigned projects from start to finish What We're Looking For: - 5+ years of professional full-stack development experience - Strong experience with React and React Native - Strong Node.js and TypeScript experience - Experience working with AWS-hosted applications - Experience with MySQL and relational database design - Comfortable working within an existing codebase - Strong debugging and problem-solving skills - Excellent written and verbal English communication - Reliable, responsive, and self-directed Bonus Points - SaaS startup experience - Hospitality or restaurant technology experience - UI/UX experience - Experience leading projects or mentoring developers - DevOps or infrastructure experience !!Important!! Communication is extremely important for this role. We are looking for someone who can communicate clearly, participate in weekly video meetings, explain technical decisions in plain English, and provide consistent updates on progress and blockers. Engagement Details: - Part-time freelance to start - Approximately 10–20 hours per week - Long-term opportunity for the right person - Direct relationship with the company (no agencies or subcontracting) When applying, please include: - A brief summary of your React Native experience - A SaaS product you've worked on that is currently live - Your availability (hours per week) - Your hourly rate - Why you think you'd be a good fit for this role Please do not use AI-generated proposals. We are looking for thoughtful, personalized responses that demonstrate relevant experience.

We are looking for an experienced Quantitative Trading Strategist / Trading Systems Lead or Senior Algorithmic Trading Developer with quant strategy experience to review an existing small-cap momentum trading bot. This is not a coding implementation role at this stage. We are looking for an independent reviewer who can analyze the bot’s backtesting results, scoring model, gate logic, tactical trigger logic, entry/exit rules, and trading workflow, then provide a clear written report with developer-ready recommendations. The full scope of work will be provided as a PDF. Project Background We have an existing small-cap momentum trading bot designed to scan U.S. equities, identify potential gappers and momentum candidates, score them using a structured 0–100 model, and prepare them for dry-run / paper-trading validation. The system includes: • Hard gates and soft gates • Wheelhouse / Just Outside Wheelhouse classification • One soft-failure rule in certain conditions • 0–100 scoring model • Structure, Momentum, Tactical Trigger, and Context scoring • Tactical Trigger confirmation before entry • Buy/no-buy decision logic • Exit and risk-management logic • Backtesting and timestamped replay results We now need a qualified trading systems expert to review whether the system is realistic, properly structured, and capable of identifying the type of small-cap momentum setups we are targeting. Main Goal The main question we need answered is: Even if the bot is built correctly according to the current rules, how should the strategy, scoring model, gates, entries, exits, and decision logic evolve to become smarter, more adaptive, and more effective in real market conditions? What You Will Review You will review: • Backtesting results • Decision trace files • Trade results • Scoring model • Hard gate and soft gate logic • Wheelhouse / Just Outside Wheelhouse rules • Tactical Trigger / candlestick logic • Entry logic • Exit and risk-management logic • Missed opportunities • False positives • Time-of-day behavior • Market-regime behavior • Whether the system is too restrictive or not restrictive enough • Whether the score threshold is realistic • Whether the bot is identifying valid small-cap momentum opportunities early enough Important Clarification This role is for an independent report and strategy review only. You will not be modifying the production code directly. The current developer will handle code changes after your review. Your job is to provide a clear, practical, developer-ready report that explains what should change, why it should change, and how it should be tested. Ideal Candidate The ideal candidate has real experience with: • Intraday equity trading systems • Small-cap momentum trading • Gap-and-go strategies • High relative volume / low float stocks • VWAP, EMA, ORB / ORH / ORL logic • Candlestick-based tactical entries • Backtesting and timestamped replay • Trade-entry optimization • Exit and risk-management logic • False-positive and missed-opportunity analysis • Translating trading strategy findings into developer-ready requirements We are not looking for someone who only gives vague trading opinions. We need someone who can review real backtesting evidence and produce a clear, practical report. Expected Deliverables Deliverables should include: 1. Backtesting Review Report 2. Top red flags from the backtest 3. Missed-opportunity analysis 4. False-positive analysis 5. Scoring model review 6. Gate logic review 7. Tactical Trigger review 8. Entry logic recommendations 9. Exit / risk-management recommendations 10. Market-regime and time-of-day recommendations 11. Developer-ready change list 12. Priority ranking of recommended changes The final report should clearly explain: • What is working • What is not working • What may be too restrictive • What may be too loose • Whether the current 85/100 threshold is realistic • Whether different entry profiles are needed • Whether exits are protecting capital properly • Whether the bot is missing good setups • Whether it is accepting poor setups • What changes should be made first First Milestone For the first milestone, we would like a 10–15 hour review. The goal of the first milestone is not to solve everything. The goal is to determine whether you can quickly identify the real issues and provide a useful, practical report. If the first milestone is successful, we may extend the work. Required Application Response Please do not send a generic proposal. In your response, please answer the following: 1. What experience do you have with small-cap momentum, gap-and-go, low-float, or high-relative-volume trading systems? 2. Have you reviewed backtesting or timestamped replay results before? Please describe. 3. Have you worked with VWAP, EMA, ORB / ORH / ORL, candlestick triggers, or tactical entry logic? 4. What would you look at first if a bot is not trading even when the score threshold is lowered? 5. What are examples of prior strategy reviews, backtest reviews, trading system reports, or developer-ready recommendations you have produced? Please provide redacted examples if available. 6. How would you determine whether the issue is scoring, gates, tactical triggers, data timing, execution readiness, or a broader strategy issue? 7. Are you comfortable providing a written report only, without directly modifying the production code? 8. What would you need from us to complete a strong first review? Screening Requirement Please include the phrase “decision trace review” at the top of your proposal so we know you read the full posting. What We Are Not Looking For We are not looking for: • A general Python developer only • Someone to rebuild the bot from scratch • Someone to directly modify production code at this stage • Someone who only provides broad trading opinions • Someone who cannot explain their review process • Someone who cannot provide examples of prior work • Someone who wants to tune thresholds without evidence

Backend Developer Needed for Consumer Caregiver App We’re building a caregiver app that helps families keep track of a loved one’s care information, including diagnoses, medications, surgeries, notes, and tasks. This is a direct-to-consumer app, not a hospital or clinic product, so we need someone who can build a secure, privacy-first backend for sensitive health data. What you’ll build: - User authentication and account management. - Care recipient profiles. - Structured health records for diagnoses, medications, surgeries, allergies, appointments, notes, and care tasks. - Role-based sharing for multiple caregivers. - Secure file storage for documents or images. - Audit/activity logging. - Export and deletion features. - Admin tools for support and account recovery. What we need: We’re looking for a backend developer who can build a clean, secure, production-ready system with strong privacy controls. Required experience: - Strong backend development experience. - Experience with Postgres and secure API design. - Understanding of authentication, authorization, and role-based access control. - Experience with encryption, secure file storage, and logging. - Comfortable working with consumer health or sensitive data. - Ability to document architecture and hand off code cleanly. Nice to have: - Experience with healthcare, healthtech, or privacy-sensitive apps. - Experience with Supabase or AWS. - Familiarity with FTC health privacy expectations for consumer apps. - Experience designing systems that can scale into stricter compliance later. Preferred stack For this project, we’re leaning toward a cost-friendly, modern stack such as: - Front end: Lovable. - Backend: Supabase or a similar managed Postgres backend. - Auth: built-in auth with strong password/session handling. - Storage: private file storage. - Permissions: row-level security or equivalent. - Optional server logic: edge functions or a small Node service. If you think a different stack is better, explain why. Security and privacy expectations: This app will store sensitive family health information, so security matters a lot. We need the backend to include: - Encryption in transit and at rest. - Strong access controls. - Minimal data collection. - No unnecessary third-party tracking or ad-tech. - Audit logs for important actions. - Secure password handling. - Private storage and restricted file access. - Clear privacy-aware architecture. Important note: This is not a hospital backend. We do not need a complex enterprise healthcare platform on day one. We do need someone who understands how to build a secure consumer health app properly, with the option to evolve later if the product grows. Deliverables: 1. A short architecture proposal. 2. Recommended stack and rationale. 3. Basic database schema. 4. Security and permissions plan. 5. Estimated timeline and budget. 6. Build the MVP backend after approval. Please send: - A short intro. - Relevant backend projects. - Any healthcare, privacy, or sensitive-data experience. - Your preferred stack. - Your estimated cost and timeline. - One example of a backend system you’ve built that required careful permissions or security.