**Job Description:** We are looking for an experienced Software Quality Engineer to enhance quality in our SaaS platform through manual testing, test automation, API validation, and collaboration across teams. This senior role focuses on building scalable quality systems rather than just executing test cases. **Core Responsibilities:** - **Quality Strategy:** Improve QA processes, establish testing standards, create risk-based testing, and drive quality metrics. - **Manual Testing:** Develop test plans, perform exploratory and regression testing, validate workflows, and document defects. - **Test Automation:** Design automated testing frameworks for UI and APIs, integrate testing into CI/CD pipelines, and enhance automation coverage. - **API Testing:** Test REST APIs, validate authentication, and create automated regression suites. - **Data Validation:** Validate application data, perform data reconciliation, investigate issues using SQL, and verify integrations. - **Documentation:** Maintain test plans, QA processes, release checklists, regression suites, status reports, and defect documentation. - **Collaboration:** Work with developers, participate in reviews, lead bug triage, and communicate quality risks. **Required Experience:** - 5+ years in QA for SaaS products - Strong manual and test automation skills - API testing experience and strong SQL skills - Agile methodology experience - Excellent communication skills **Preferred Experience:** - Familiarity with AI tools for QA processes - Experience with B2B SaaS platforms, enterprise software, and complex workflows **Automation Tools:** Playwright, Cypress, Selenium, TestCafe **API Tools:** Postman, Swagger/OpenAPI **Data Validation:** SQL Server, PostgreSQL, MySQL

Hi - I work at a small consulting firm. We are looking to learn and leverage AI for our outbound sales efforts. Clay seems to be an interesting tool for creating alerts for timely marketing. More importantly, it can add contextual personalization for outbound as well. There are probably other use cases and likely other tools that can be used. We are looking for some expertise in Clay, other tools and best practices to modernize our outbound. The engagement could just be setting up some workflows, alerts, integrations, etc. It could be managing adjustments in the future or providing guidance for a more turnkey effort. TBD here... You must be an expert in Clay first. We use Salesloft, Salesforce, Zoominfo, Navigator, etc already. Lets start with an initial call to see if this works. Thanks.

DO NOT SEND AN AI GENERATED PROPOSAL. READ THROUGH THIS POST AND GIVE US YOUR HUMAN RESPONSE. Location: Remote Team size: Small (you’ll know everyone’s name) Stack: Java 21 / Guice / Gradle backend + React 19 / TanStack / MUI frontend **To apply** 1. Give us a few sentences for why you're a fit for the description below. 2. Include a Github/Gitlab/Gitea link to a recent PR you’re proud of (any language) 3. 5–10 minute Loom of you using Claude Code on a real task. **About the role** QAction is a large-scale Java enterprise document, records, and workflow platform — multi-project Gradle build, ~15 modules, customer-specific deployments (USDA, Ditco, Ascension, Mayo). The backend is being modernized behind an OpenAPI v2 surface (oasv2); the frontend is being rebuilt off GWT onto React 19 + TanStack Router/Query/Start with MUI v7. We need a developer who’s equally comfortable extending a v2 endpoint in a Guice-wired Java service as they are wiring up a TanStack Query call behind a Lexical editor or a virtualized data table — and who treats Claude Code as a peer on the keyboard, not a novelty. You’ll work directly with the product lead. No layers, no JIRA theater. Ship, review, iterate. **What you’ll do** Own vertical slices end-to-end: OpenAPI spec → Manager/ManagerImpl + EndpointImpl in QAction Java → React 19 / TanStack Query UI → JUnit + Playwright coverage. Extend the QAction Java backend: Guice (constructor injection only), Hazelcast-aware code paths, customer-deployment-aware module wiring, JUnit under oasv2. Build Modern UI features in the React 19 stack: TanStack Router/Query/Start, MUI v7 + Emotion, React Hook Form + Zod, Lexical, dnd-kit, OIDC auth (oidc-client-ts), TypeScript with the wrapper-component discipline already in place (Button, Icon, LabeledObject, ScrollShadows, etc. — never raw MUI in features). Move features off GWT onto the React 19 stack one slice at a time, without breaking the legacy app. Pair with Claude Code daily — write prompts that ship code, review agent diffs critically, and improve our skills/agents library when the workflow has friction. Keep integration tests honest: real DB + Solr + Keycloak at the seam, not mocks. Tech direction you’ll be living in **Backend** Java 21, Gradle multi-project (build single modules — ./gradlew QAction:build — never clean build) Guice DI, constructor injection, Manager/ManagerImpl naming (we don’t use “Service”) OpenAPI-first v2 endpoints in oasv2, canonical error model, paginated response classes as standalone beans in oasv2.beans Hazelcast clustering, Solr search, Postgres/MSSQL, Keycloak/OIDC FileNet integration, document import/migration tooling, RMT/remote services **Frontend** React 19 + TypeScript, Vite 7, TanStack Router + Query + Start + Table MUI v7 + Emotion, MUI X Date Pickers + Tree View Lexical (rich text), @dnd-kit + Atlaskit pragmatic-drag-and-drop, react-virtualized, react-pdf React Hook Form + Zod, oidc-client-ts + react-oidc-context, notistack, pino File naming kebab-case, @/ path imports, theme-first styling, wrapper components over raw MUI Adjacent surfaces in scopes over time **What we’re looking for** 8+ years shipping production app code across backend and frontend. You’ve owned services and UIs, not just one or the other. Java fluency — Guice or Spring DI, REST/OpenAPI design, JUnit. Bonus if you’ve worked in a 1M+ LOC enterprise Java codebase with customer-specific module deployments and didn’t flinch. Modern React fluency — React 18/19, TypeScript, TanStack Query (or React Query), a real opinion about effect dependency graphs, comfort with virtualized tables and rich-text editors. OpenAPI-first thinking. Specs are the source of truth, not documentation written after the fact. Claude Code power user. You write prompts that delegate well, you know when to use a subagent vs. inline, you’ve built or extended skills/hooks/MCP integrations. You can show us a recent session where Claude shipped something non-trivial under your direction. Small-team temperament. You’re allergic to ceremony. You read code before asking. You raise a small PR when it’s ready. **Nice to have** GWT (you won’t write new GWT, but you’ll need to read and migrate it). Workflow / BPMN, records management, e-signature, or ECM domain experience. Hazelcast, Solr, Keycloak operational familiarity. Lexical or another modern rich-text editor. Playwright (you’ll inherit a calibrated suite — we want you to improve it, not rewrite it). Docker compose stack bring-up across Postgres, MSSQL, Solr, Keycloak. Python services or Helm/Kubernetes deployment experience. **How we work** Small PRs. Every change ships through review. If it’s getting big, split it. Test-driven design. Tests come with the code, not after. JUnit on the Java side, Vitest + Playwright on the React side. Daily standups. 15 minutes, async-friendly, but we show up. Memory-backed Claude Code sessions — agents learn the codebase with you, not against you.

Overview We run a high-volume B2B cold email program for a national background screening company. The infrastructure is built and live. We need an experienced operator to take full ownership — running the system, maintaining deliverability, managing lead pipelines, and continuously improving performance. This is not a setup job. This is an ongoing management role for someone who already knows these tools and can hit the ground running with minimal handholding. What You'll Own Lead Sourcing & Scraping — Build and manage Apify scraping workflows to pull targeted prospect lists from the right sources. You understand what makes a list clean versus garbage, and you enforce quality before anything touches an inbox. Email Infrastructure — Manage sending domains and inboxes in Scaledmail and Instantly. This means monitoring domain health, rotating inboxes appropriately, maintaining warmup, and keeping bounce rates low. You know what a burned domain looks like before it's actually burned. Automation & CRM Integration — Maintain and improve Make.com workflows that move verified leads from sourcing → enrichment → Instantly → HubSpot. Automations must be reliable and auditable. You're comfortable debugging broken scenarios and building new ones. Email Verification — Manage AnyMailFinder to verify contacts before they enter any sending sequence. You understand verification thresholds and make judgment calls on borderline lists. Campaign Management — Different sequences go to different audiences. You'll manage which contacts flow into which campaigns, monitor performance, and make copy or sequencing adjustments based on what the data shows. Reporting — Weekly summary of key metrics: open rates, reply rates, bounce rates, domain health, inbox placement, leads delivered to HubSpot. Flag issues before they become problems. This Role Is Right for You If: You've managed cold email programs at 30K–100K+ emails/month and know what breaks at scale You treat deliverability as non-negotiable — domain reputation is something you protect, not react to You're a systems thinker who builds processes that don't require babysitting You proactively flag when something looks off — you don't wait to be asked You can look at reply rate and bounce data and know what to adjust without being told You've personally managed Instantly, Apify, Make.com, Scaledmail, and AnyMailFinder — not just heard of them Hard Requirements Hands-on experience with Instantly (inbox management, campaign structure, sending limits, warmup) Hands-on experience with Apify (building or running scraping actors for lead generation) Hands-on experience with Make.com (multi-step automation scenarios, error handling, webhook flows) Experience with AnyMailFinder or comparable verification tools (not just "I've used email verification") HubSpot CRM experience — contacts, lifecycle stages, list management, basic workflow logic Demonstrated ability to keep bounce rates under 3% at volume English fluency — you'll be reading and interpreting campaign data and communicating findings clearly Nice to Have Experience with B2B lead generation for HR, workforce, or compliance-adjacent industries Copywriting or sequencing instincts — you can spot a weak subject line or a broken CTA Experience managing multiple client programs simultaneously (you know how to context-switch without dropping balls) To Apply Please include in your proposal: A brief description of the largest cold email program you've personally managed (volume, tools, outcomes) Your approach to maintaining deliverability at scale — specifically what you monitor and how often One example of an automation or workflow you built in Make.com for a lead gen or email program Your current availability (hours/week) and any other active commitments Proposals without these four items will not be reviewed. A note on fit: We're not looking for someone to check boxes. We want someone who treats this program like it's their own — who notices when something's underperforming and already has a fix in mind before we ask. If that's not how you work, this isn't the right role.

We are a mobile app in the Astrology & Self-Discovery niche. We are looking for a sharp, trend-savvy, and highly organized Creative Strategist / Scriptwriter based in the US to help us scale our user acquisition through high-converting video creatives (TikTok, Instagram Reels, Shorts, Threads). What we are NOT looking for: We love creativity, but we don’t need an artist who relies solely on "inspiration" and random ideas. What we ARE looking for: We need a systematic thinker. Someone who treats creative production like a science. You know what hooks are trending right now, but more importantly, you know why they work and how to seamlessly bridge a viral hook into the actual app interface and product value, rather than just gluing them together. You don't need to be an AI expert out of the box, but you must be open to learning and adapting. If you are deeply structured, everything else can be easily taught. Key Responsibilities: Trend Hunting & Hook Library: Continuously monitor TikTok/Reels trends. Maintain a structured database (Google Sheets/Notion) of hooks, categorized by performance, what’s been tested, what worked, and what failed. The database (the structure) can be provided by us! Scriptwriting & Storyboarding: Write engaging, high-retention video scripts for creating marketing creatives. Product Integration: Ensure the video doesn't just "drop" after the hook. You will design the narrative flow so the trend naturally reveals the app’s features and drives downloads. Creative Iteration: Produce multiple variations of scripts for a single product to test different angles, concepts, and hooks. Requirements: Location: US-based (native English speaker with a deep understanding of US internet culture and Gen Z/Millennial slang/trends). Niche Interest: Passion for or deep understanding of Astrology, Tarot, Psychology, or Self-Discovery topics. Systematic Approach: Obsession with structure. You love tables, tracking sheets, and organizing your thoughts logically. Experience: Proven track record of writing video scripts for paid social (Meta, TikTok) or organic viral content. Growth Mindset: Coachable, open to feedback, and willing to learn new tools (including AI workflows if needed).

We are seeking a US-based computer vision and full stack developer to build a platform for sports card recognition. The project includes developing subscription management, dashboards, and user account features. The ideal candidate will have experience creating scalable applications and integrating computer vision capabilities into a user-friendly platform. Hiring: Computer Vision + Full Stack Developer for Sports Card Live Auction Overlay App (SaaS) 📌 Overview I’ve built an MVP of a real-time sports trading card scanning and comping overlay tool using Loveable.dev. The product helps buyers gain an edge during live auctions by instantly identifying cards and showing real-time market comps. Now I’m looking for a U.S.-based developer (or strong US-aligned freelancer) to take this from MVP → production SaaS. This is a subscription-based product, so I need someone who can help build something fast, accurate, scalable, and hard to replicate. 🧠 What the product does Users can: Capture or upload sports trading card images during live auctions (mobile + desktop) Instantly identify: Player Year / set Parallel / serial number Pull live market comps Display a real-time “buy / avoid / fair price” overlay The goal is speed + accuracy in live buying situations (seconds matter). ⚙️ What I already have MVP built in Loveable.dev Basic overlay + UI flow Initial comp logic concept Subscription idea (not yet fully implemented) 🛠️ What I need help building (Phase 1 → Scale) I’m looking for someone to help rebuild and harden the system into a real SaaS product: 1. Computer Vision / OCR Layer Card detection from images (mobile + desktop) OCR extraction (player name, set, serial numbers) Image recognition / matching to known cards Confidence scoring (very important — must avoid wrong matches) 2. Comp Engine (Core Value) Integrate or build system for: eBay sold listings 130point or similar comp sources Card Ladder / ALT-style pricing logic Return: last sale average comp trend direction liquidity estimate 3. Real-Time Overlay System Lightweight overlay that works during live auctions Low latency (fast lookup is critical) Works on mobile + desktop workflows 4. SaaS Infrastructure User accounts + authentication Subscription billing (Stripe) Usage tracking / rate limiting Admin dashboard 5. Scaling / Production Hardening API architecture improvements Database structure Performance optimization for real-time use Error handling for imperfect images 💡 Ideal candidate You should have experience with: Computer vision (OpenCV, YOLO, or similar) OCR pipelines AI image classification or similarity matching Full-stack SaaS development Stripe subscriptions API design (Node.js / Python / Next.js preferred) Huge plus if you have: Sports card / collectibles knowledge Experience with marketplaces or scraping pricing data Real-time / low-latency systems 🎯 Why this is interesting This is not a generic app. It’s: A real-time decision engine for high-value collectibles Built for a passionate, high-spend niche (sports cards) Subscription-based with strong monetization potential Designed for speed advantage in live auctions 📍 Requirements Must be U.S.-based (preferred for communication/time zone alignment) Must be able to work independently Must have strong GitHub/code examples Bonus if you’ve built AI or vision-based SaaS tools before 💰 Budget Open to: Hourly or fixed project 📩 To apply, please include: Relevant CV / GitHub Past AI / computer vision projects Any SaaS or startup experience Your approach to building a real-time image → comp system Availability per week

Seeking a freelancer to streamline personal systems for a small firm. The task involves optimizing processes using ASANA, Google Cal blocks, RECLAIM, calendar issues, SuperHuman Email efficiency and HUBSPOT integration Software. This is a one-time project aimed at enhancing efficiency and organization. Ideal candidates will have experience in administrative support and email communication.

EroFlow Intelligence is an enterprise-grade, autonomous AI orchestration pipeline designed to mitigate global supply chain disruptions for aerospace manufacturing. Built using a multi-agent framework, the system automates the entire lifecycle of risk detection, impact analysis, and procurement mitigation without requiring human intervention for standard operational anomalies. The architecture coordinates three specialized, asynchronous AI agents that communicate via a centralized event bus to solve complex logistical bottlenecks in real-time. Core Agent Architecture & Workflow 1. The Sentinel Agent (Data Ingestion & Extraction) Role: Continuous Global Monitoring. Function: Utilizes advanced LLM-driven web scraping and unstructured data extraction to monitor global news feeds, geopolitical shifts, weather anomalies, and shipping port telemetry. Trigger: If it detects a disruption (e.g., a port strike or critical mineral shortage), it extracts key entities (materials affected, estimated delay times) and passes a structured JSON payload to the orchestration layer. 2. The Impact Assessment Agent (Predictive Modeling) Role: Deep Cross-Referencing & Analytics. Function: Upon receiving a trigger, this agent cross-references the disrupted material with the company’s internal ERP (Enterprise Resource Planning) database and current inventory levels. Output: It runs a predictive analysis to determine exactly which production lines will stall and calculates the financial risk, assigning a high/medium/low priority score to the event. 3. The Mitigation & Logistics Agent (Autonomous Execution) Role: Operational Resolution. Function: If the risk score exceeds a specific threshold, this agent is authorized to take action. It autonomously queries pre-vetted alternative suppliers via APIs, negotiates standard volume pricing based on historical contract data, drafts a comprehensive procurement proposal, and queues the purchase order for final human sign-off (or executes it automatically if under a certain dollar cap). Technical Stack (The Blueprint) Frameworks: LangGraph / CrewAI (for multi-agent state management and deterministic routing). Core Language: Python 3.11+ Data Layer: PostgreSQL (for ERP syncing) & Pinecone / Qdrant (Vector database for storing and querying supplier contract PDFs and historical compliance documentation). LLM Orchestration: OpenAI GPT-4o / Anthropic Claude 3.5 Sonnet utilized via structured outputs (Pydantic parsing) to ensure strict API data integrity. Hosting & DevOps: Containerized via Docker, orchestrated via Kubernetes, and deployed on AWS with asynchronous task queues managed by Celery and Redis. Quantifiable Business Results (The Hook) 92% Reduction in supply chain anomaly response time (from 48 hours down to 14 minutes). Automated Recovery: Successfully mitigated over 140 potential production line stalls autonomously in simulated stress tests. Cost Efficiency: Saved an estimated $1.2M in expedited shipping fees by predicting bottlenecks 10 days before they impacted manufacturing floors.

We're a growing service company looking for an experienced developer to build a Slack bot that answers employee questions about our HR policies, SOPs, and internal documentation. Team members will tag the bot in a channel, ask a question in plain language, and receive a conversational, accurate answer grounded in our documented materials. **This is a build + teach engagement.** I have no coding background, and a core requirement of this project is that you walk me through your decisions and architecture as you build, so I can understand, maintain, and eventually extend the system myself. If you're a strong developer but don't enjoy explaining your work, this isn't the right fit. ## What You'll Build A production-ready Slack bot with the following architecture: - **Slack integration** using Slack's Bolt framework (Python or Node.js — your recommendation welcome) - **Retrieval-Augmented Generation (RAG)** pipeline: questions are matched against our documentation via semantic search, and relevant context is passed to an LLM for a conversational answer - **Vector database** (Pinecone, Weaviate, or a comparable option you can justify) storing embeddings of our policies, SOPs, and transcripts - **OpenAI API** integration for embeddings and chat completions - **Document ingestion pipeline** that can handle multiple source formats: Word docs, PDFs, spreadsheets, and plain-text transcripts (e.g., exported Loom video transcripts) - **Source citations** in bot answers, so users can see which policy or document the answer came from - Deployment to a cloud environment (AWS, Heroku, Railway, or similar) with clear instructions for how it runs and how to restart or update it ## Technical Requirements You should have demonstrable experience with: - Slack app development (Bolt framework, event subscriptions, OAuth/permissions setup) - OpenAI's API (chat completions and embeddings) - RAG architecture and vector databases (Pinecone, Weaviate, Qdrant, pgvector, or similar) - Python or Node.js backend development - Cloud deployment and basic DevOps (environment variables, API key security, uptime) **In your proposal, please link to or describe at least one similar project you've built** — ideally a Slack bot, a RAG system, or an LLM-powered internal tool. ## Deliverables 1. A working Slack bot deployed to production and connected to our Slack workspace 2. Document ingestion process (with instructions or a simple tool for me to add new documents myself as our documentation grows) 3. Full source code in a repository I own, with clear comments 4. **Written documentation** covering: system architecture, how each component connects, how to add/update documents, how to update API keys, and common troubleshooting steps 5. **Teaching sessions**: recorded screen-share walkthroughs (or live calls) at each major milestone explaining what was built and why — I estimate 3–5 sessions of 30–60 minutes 6. A handoff session at the end where we test the bot together and review maintenance procedures ## Communication & Working Style - Regular progress updates (at minimum, 2x per week) - Willingness to explain decisions in plain English, not just technical jargon - Patience with beginner questions — teaching is part of the paid scope, not a favor - Fluent written and spoken English - Availability for scheduled video calls (please note your time zone in your proposal) ## Scope Notes - Initial document set is modest, but the system should be designed to scale as our documentation library grows significantly - Future phases may include: automatic transcript ingestion from Loom, additional Slack channels/workflows, and analytics on what questions get asked — mention if you have experience with any of these - I will provide: Slack workspace admin access, OpenAI API account, and all documentation to be ingested ## How to Apply In your proposal, please include: 1. A brief description of a similar project you've built (links or screenshots appreciated) 2. Your recommended tech stack for this project and a one-paragraph explanation of why 3. Your approach to the teaching/documentation component 4. Estimated timeline and total cost (fixed price preferred; open to milestone-based payment) 5. Your time zone and general availability Proposals that are clearly personalized and address the teaching component will be prioritized. Generic copy-paste proposals will be declined.

We recently migrated our high-volume moving sales call center to RingCentral CX and are looking for an experienced consultant to help us maximize the platform. We are not looking for basic phone system setup. We need someone who can review our current environment and recommend improvements to increase sales performance, conversion rates, agent productivity, and overall efficiency. Our goals include: * Optimizing inbound call routing and lead distribution * Reducing missed and abandoned calls * Improving speed-to-lead * Configuring and maximizing RingCentral AI features * Building management dashboards and KPIs * Improving agent accountability and performance tracking * Reviewing QA and coaching opportunities * Integrating workflows with our CRM (Granot) Please describe: * Your experience with RingCentral CX / RingCX * Similar contact center projects you have completed * Results you helped achieve * Your approach during the first 30 days Bonus if you have experience with sales call centers, lead generation, home services, insurance, mortgage, or moving companies. To confirm you read this posting, please start your proposal with the words: "RingCX Review".