About the Role: We are seeking a highly qualified Senior Machine Learning and Natural Language Processing Engineer with deep expertise in sentence parsing, contextual understanding, categorization, and language extraction to support and advance Sybal’s Proof of Governance® (PoG™) platform. This role blends advanced NLP engineering, full-stack development, and enterprise-grade deployment. You will design custom NLP models, build scalable AI-driven services, and deploy production-ready applications that transform raw policy and technical language into structured governance intelligence. You must be a senior-level full-stack engineer proficient in Python, Django, JavaScript, HTML, and CSS, with the ability to dockerize and deploy applications into production environments. Experience commercializing enterprise AI applications is required. You should also be familiar with using agentic AI tools in a development context—for debugging, workflow acceleration, rapid prototyping, and improving engineering efficiency. ________________________________________ Key Responsibilities: NLP & Machine Learning Engineering: • Build advanced NLP models for sentence parsing, context detection, semantic analysis, entity extraction, and policy language interpretation. • Develop hybrid ML + rule-based systems that support governance modeling and policy decomposition. • Create pipelines for text ingestion, annotation, categorization, and structured language extraction. • Design evaluation frameworks for accuracy, drift, reliability, and linguistic precision. • Research and implement non-LLM NLP methods relevant to governance and policy analysis. Full-Stack Engineering: • Develop production-ready applications using Python (spaCy, NLTK, TensorFlow, or PyTorch to build and optimize NLP models), Django, JavaScript, HTML, CSS, and modern tooling. • Further develop NLP models for PoG™ Feature enhancements. • Develop and maintain secure, scalable REST APIs and backend services. • Integrate ML components seamlessly into PoG™’s architecture. Production Deployment & DevOps: • Dockerize machine learning pipelines and full-stack applications for uniform deployment. • Deploy and manage services in cloud production environments (AWS, GCP, or Azure). • Set up CI/CD pipelines, monitoring, observability, and scalable containerized processes. • Ensure production performance, uptime, and system reliability. AI Automation for Engineering Efficiency: • Use agentic AI tools to assist with debugging, test generation, workload orchestration, and internal development workflows. • Integrate AI-assisted coding tools responsibly into engineering processes. Contribute to the Proof of Governance® Platform: • Build NLP and ML components that strengthen PoG™’s ability to: • Map policy language into structured governance data • Detect enforceability gaps • Identify policy dependencies and contextual interactions • Deliver measurable, enforceable governance intelligence • Collaborate with PoG™ architects to extend platform intelligence across governance domains. ________________________________________ Qualifications: Required Skills & Experience: • 6–10+ years of software engineering experience with specialization in ML and NLP. • Mastery of sentence parsing, syntax/semantic analysis, dependency modeling, and contextual extraction. • Proven experience commercializing enterprise AI or ML-driven applications. • Proficiency in: o Python o Django o JavaScript o HTML / CSS • Demonstrated ability to dockerize applications and deploy them into production. • Strong understanding of ML architecture, data modeling, distributed systems, and backend engineering. • Experience using agentic AI tools for engineering workflows (debugging, code analysis, test generation). • Strong cloud engineering experience (AWS, GCP, Azure). Preferred Qualifications: • Background in computational linguistics or structured policy analysis. • Experience with ontologies, taxonomies, or governance modeling. • Prior work in regulated, audit-heavy, or mission-critical environments. • Contributions to high-scale enterprise software platforms. ________________________________________ Who You Are: • You excel in both advanced NLP engineering and full-stack software development. • You can design systems end-to-end—from custom algorithms through front-end integration to production deployment. • You understand how to use AI to accelerate development processes. • You are driven by building systems that transform governance from assumption to measurable, enforceable proof. • You are excited to contribute to the continuous evolution of PoG™

I’m building Elevyn, a platform designed to help people better understand themselves through connected data, intentional reflection, and AI-generated insights. This is not a social media platform. This is not a productivity app. This is not just another trading journal. Elevyn is an operating system for self-mastery, with trading serving as the first environment where personal growth becomes measurable. Most apps collect data. Elevyn is designed to observe. The goal is to connect information across different areas of a person’s life and uncover meaningful patterns that help them improve their decision-making, habits, discipline, and overall performance. The Vision Users will log information such as: • Sleep • Mood • Daily reflections • Workouts • Morning routines • Trading activity • Goals • Habits • Personal notes Instead of simply displaying this data, Elevyn will analyze relationships between it and surface meaningful insights. Examples include: • “You slept less than 5 hours before 7 of your last 10 losing trades.” • “Your win rate increases after completing your morning routine.” • “You tend to become more impulsive after multiple winning days.” • “Your consistency improves when workouts and journaling happen on the same day.” The long-term vision is an intelligent system that continuously helps users become more self-aware. Current Stage I already have: • Brand identity • Vision and philosophy • User flows • Interactive prototype • Core feature planning • Long-term roadmap I’m now looking for a developer or small team (2-3 people) to build the first production version. What I’m Looking For I’m looking for someone who can think beyond simply building screens. I want someone who can: • Build scalable architecture • Recommend the best technologies • Think through user experience • Ask thoughtful questions • Help solve technical challenges • Build for future AI integrations • Create clean, maintainable code Experience with AI, analytics, mobile applications, and scalable backend systems is a significant advantage. Technology (Open to Recommendations) I’m open to your recommendations, but I’m considering: • Flutter or React Native • Node.js or Python backend • PostgreSQL • Firebase/Supabase • AWS • AI integrations (OpenAI or similar) • Secure authentication and cloud infrastructure Long-Term Vision Trading is only the beginning. The underlying engine should eventually support entrepreneurs, athletes, creators, students, and anyone pursuing mastery in a specific area of life. The core idea remains the same: Help people understand themselves by connecting patterns across their behaviors, decisions, and outcomes. Who I’m Looking For I’m looking for someone who believes in building meaningful products—not just completing tasks. If you’re excited about creating a platform that combines psychology, data, AI, and personal development into something people genuinely use to improve their lives, I’d love to hear from you. Please include examples of similar work, your recommended tech stack, and how you would approach building a scalable MVP that can grow over time.

I'm a retired entrepreneur and active investor looking for a skilled Claude AI practitioner to serve as a private tutor and advisor. I use Claude regularly and have a working Microsoft 365 integration in place, but I want an experienced guide to help me unlock advanced capabilities and build efficient, reusable workflows tailored to my work. This is not a beginner engagement. I learn quickly, prefer direct feedback over hand-holding, and want sessions focused on my actual use cases — not generic training. Topics to Cover - Claude Projects — structure and strategy for ongoing, organized work - Investment and general research — synthesizing company, market, and topic information efficiently - Correspondence — drafting polished emails in Outlook that match my voice with minimal editing - Document analysis — extracting key information from legal, financial, and fund documents - Microsoft 365 add-ins — what's available and genuinely useful for Word, Excel, and PowerPoint - Voice input and dictation — getting started and optimizing as a primary input method - Workflow building — creating persistent, reusable tools rather than starting from scratch each session - Agents, skills, and connected tools — connecting external tools, leveraging agentic capabilities, and building autonomous workflows - Prompt craft — advanced techniques applicable across all of the above Ideal Candidate - Hands-on experience with Claude (not just ChatGPT or general AI) - Background working with business operators, investors, or executives — not primarily developers or academics - Can demonstrate real-world applications, not just theoretical knowledge - Comfortable moving at a fast pace and adapting sessions to my priorities Format Virtual sessions via video call, 60–90 minutes each. Frequency to be determined based on fit and progress. Looking to begin with 4–6 sessions and reassess. To Apply Please include: 1. A brief description of your hands-on experience with Claude specifically 2. One or two examples of business or executive use cases you've worked on 3. Your availability and hourly rate A short introductory call before committing to paid sessions is expected.

We are seeking a skilled software developer to finialize our Software development and create a multi-agent orchestration platform. The role involves fininalizing/creating our software development of out Ai-Native TMS, creating a multi-agent orchestration platform that creates all necessary agents to improve system reliability, and optimizing performance. The ideal candidate will have experience in software development and a strong understanding of multi-agent systems. You will work closely with our team to ensure seamless integration and deployment of new features.

Eligibility: This role is open to U.S. citizens only due to client security and compliance requirements. Please apply through this posting only — do not contact Data-Sleek directly regarding this position. Applications received outside this channel will not be considered and reported to Upwork. Data-Sleek is looking for a Senior AI Solutions Engineer to lead our on-premise and government-cloud AI deployments. You will design, build, and deploy AI-powered data pipelines for clients who cannot use commercial cloud due to ITAR, CMMC, or other data residency constraints, beginning with a client in the aerospace and defense sector. Beyond this first engagement, you will become Data-Sleek's go-to engineer for AI deployments across defense and aerospace clients, building the practice rather than just executing a single project. About Data-Sleek Founded in 2020, Data‑Sleek® is a U.S.-based AI and data consulting firm that helps mid-market companies build the data foundation that AI actually runs on. We own the full path — data strategy, architecture, integration, warehousing, and AI implementation — so organizations can adopt AI with confidence, stay compliant, and scale, without first hiring an internal data team. Our distributed U.S. team (San Francisco, Los Angeles, Irvine, Dallas, Chicago, and New York) partners with clients across healthcare, finance, insurance, logistics, and technology, modernizing data platforms with best-in-class tools like Snowflake, dbt, Fivetran, Tableau, and AWS. Trusted by Fortune 500 institutions and growing companies alike, Data‑Sleek turns complex data into measurable outcomes — faster insight, lower cost, and AI projects that deliver. About the Role You will own the technical delivery of AI-powered data pipelines in restricted environments where commercial cloud is not an option. The immediate engagement centers on a Product Lifecycle Management (PLM) data migration: building a pipeline that connects to a client's SharePoint on a restricted Microsoft 365 government tenant, reads engineering documents, classifies and summarizes them, detects duplicates, and rates naming-convention compliance to produce a migration-readiness report. You will start on-premise, then help the client evaluate and move to government cloud for production. Key Responsibilities AI Pipeline Development Build AI pipelines that connect to a client's SharePoint on a government cloud tenant, read engineering documents, classify them by type, generate summaries, detect duplicates, and rate naming-convention compliance in support of PLM data migration. Catalog large document repositories and produce migration-readiness reports and Excel catalogs that give clients a clear, measurable picture of their data. Engineer document-parsing workflows across DOCX, PDF, and XLSX formats, including embedding generation and database operations. On-Premise & Government Cloud Deployment Deploy on-premise first — a Mac Mini running Gemma via Ollama — standing up, serving, and tuning local inference infrastructure. Evaluate and migrate to production on Azure OpenAI (Azure Government) or AWS Bedrock (GovCloud) when the client is ready to scale. Keep deployments compliant within ITAR-sensitive, restricted-network boundaries throughout. Architecture & Cost Advisory Produce cost models and architecture recommendations that help client IT teams make informed platform decisions based on measured data, not vendor pitches. Compare deployment options — local, Azure Government, and AWS GovCloud — on cost, performance, and compliance, and explain the trade-offs clearly. Practice Building & Delivery Serve as Data-Sleek's go-to engineer for AI deployments across defense and aerospace clients. Build a reusable capability — a repeatable AI-solutions practice — rather than executing a single one-off project. What You Bring Required U.S. Citizen: U.S. citizenship is required and non-negotiable due to ITAR and client security and compliance requirements. Production LLM deployment: You have stood up inference infrastructure — not just called an API. You've handled model loading, memory constraints, failure modes, and throughput tuning in a real deployment. Local inference: Ollama, vLLM, llama.cpp, LM Studio, or TGI. You've served open-source models (Gemma, Llama, Mistral) on local hardware. Cloud AI platforms: Azure OpenAI or AWS Bedrock — at least one. Service configuration, model access, authentication, and token-based pricing. Python: Pipeline engineering — document parsing (DOCX, PDF, XLSX), API integrations, embedding generation, and database operations (SQLite, Postgres). Experience: 5+ years post-degree in software engineering, data engineering, or ML engineering. Strong Preferences Microsoft ecosystem: Entra ID, Microsoft Graph API, and SharePoint REST API at the API level. GCC High experience is a bonus. MCP (Model Context Protocol): Experience building or consuming MCP servers — a significant plus for a fast-evolving protocol. Workflow orchestration: n8n, Temporal, Airflow, or similar. The pipeline is orchestrated, not scripted. Government cloud awareness: Understanding of what FedRAMP High, IL4/IL5, and ITAR mean for cloud architecture decisions. Embeddings & vector similarity: sentence-transformers, pgvector, Qdrant, or FAISS for duplicate detection. 
Bonus (valued if present) Aerospace or defense experience: Familiarity with ECOs, BOMs, and AS9100 saves ramp time. Apple Silicon optimization: MLX, Metal acceleration, and Ollama tuning on M-series chips. Agentic frameworks: Bedrock AgentCore or Azure AI Foundry — the future direction involves agentic AI workflows on government cloud. What This Role Is Not Model training or fine-tuning. This is deployment engineering, not research. Data science or statistical modeling. The AI here is document understanding and classification, not predictive analytics. Frontend development. The deliverable is an Excel catalog and a report, not a web app. Sales or client acquisition. Data-Sleek's leadership manages the client relationship; you focus on delivery. Engagement & Compensation Remote, US-based. Occasional on-site travel to client facilities for hardware deployment and workshops may be needed. An average of 2–3 trips for the first engagement may be possible. Compensation. $40-$55/hour Why Join Data-Sleek? At Data-Sleek, you'll lead AI deployments in environments most engineers never touch — government cloud and on-premise systems where commercial tools simply aren't an option. Your work will directly shape how defense and aerospace clients adopt AI, and you'll build a reusable capability the company grows around. We focus on doing the right thing architecturally rather than selling the most expensive option, and we give our engineers the autonomy to deliver real solutions for real constraints. How to Apply If you've shipped real LLM deployments with real constraints, we'd like to hear from you. Please submit: Your resume A brief note describing one LLM deployment you've shipped — what model, what infrastructure, what data source, and what went wrong. Data-Sleek® is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all contractors.

Need a freelancer to install and configure a Chatbase AI chatbot on a local service business website. Project Scope: * Install a pre-built Chatbase chatbot on the client’s website. * Configure lead capture to collect: * Name * Phone number * Email address * Service requested * Project details * Project timeline * Configure email notifications so the client receives new lead information automatically. * Verify the chatbot is functioning correctly on desktop and mobile devices. * Test the lead capture process from start to finish. * Provide screenshots or a brief walkthrough showing successful installation and testing. Requirements: * Experience with WordPress websites. * Experience installing website chat widgets or AI chatbots. * Familiarity with Chatbase is preferred. * Ability to troubleshoot website integration issues. * Strong communication and ability to complete projects quickly. Deliverables: 1. Chatbot installed and visible on the website. 2. Lead capture functioning correctly. 3. Email notifications functioning correctly. 4. Successful test lead submitted and verified. 5. Brief documentation of what was completed. Expected turnaround: 3 business days.

Developer Scope of Work Project Overview & Engagement Terms Domexa Labs for MyCondoCompliance (mycondocompliance.com). MyCondoCompliance is an enterprise and consumer-facing web platform built to aggregate, OCR, analyze, and report on condominium association compliance data throughout Florida (starting with Miami-Dade County). 1. Key Engagement Expectations: Dedicated Weekly Support: We require reliable, continuous development capacity week-over-week to support platform growth, new features, maintenance, and internal system updates. Flexible Monthly Hours: Hours will flex on a month-to-month basis depending on business priorities, product release cycles, and current backlogs. Minimum 2-3 hours/week, not to exceed 15hrs/week. Rapid Turnaround & Steady Communication: We operate in a fast-paced environment. Quick turnarounds on hotfixes, active updates on tasks, and daily/structured communication are critical. Language Requirement: Excellent, professional verbal and written English is a strict requirement for technical syncs, documentation, and coordination. 2. Technical Infrastructure & DevOps Architecture The MVP is complete, live, and deployed. You will inherit the following technical ecosystem: Infrastructure Stack: - Code Repository: Managed via GitHub. - Front-end Hosting: Deployed and managed on Netlify. - CI/CD: Automatically triggers deployment to production on master branch updates, and to staging/dev on dev branch updates. - Back-end Hosting & Infrastructure: Managed on Digital Ocean inside a Kubernetes environment. - DNS Administration: Managed on Digital Ocean. - Third-Party API Integrations: - Mapbox: Powers map-based search and property discovery. - Mailgun: Handles transactional email delivery. - Chatbase: Integrated for natural language querying and chat functionality. - TipTap: Rich text editor powering board notes and internal editing. 3. Scope Evolution & Core Pipelines As our incoming developer, you will be expected to maintain, debug, and expand upon the core features built during our initial execution phases. A. Data Pipelines & OCR Ingestion Engine - Website Scraper/ETL: Continuous ingestion pipelines that pull structured condo data and metadata from county public registers. - Normalization Engine: Ingestion pipeline that categorizes incoming unstructured documents into strict schemas - OCR & Vectorization: All ingested documents are automatically processed via an OCR layer, and the resulting plaintext is indexed into a vector database for semantic search and Retrieval-Augmented Generation (RAG). B. Autonomous AI Processing Agents We run specialized Python/Node microservices to process aggregated document metadata: - Granular Extraction: AI agents systematically query vector databases to extract critical datapoints - Audit Trails & Provenance: Each extracted datapoint must carry verification properties—linking back directly to the document source, specific page/snippet, and extraction timestamp. C. Portal Tiering & Client Features - Consumer Interface: Detailed property pages, dynamic scoring components, PDF report compilation and downloads. - Enterprise Interface: Multi-tenant web app allowing real estate, financial, and legal clients to access deep search, structured list filtering (e.g., filtering condos by unit counts, reserve posture, specific clauses such as "Kauffman language", and termination criteria), and batch export controls. - Admin Dashboard: Tracks user engagement metrics, domain lookups, purchase histories, and mailing list extractions.

We are a small software development team actively using Claude and GitHub Copilot for development on an ASP.NET and Azure technology stack. We’re looking for an experienced AI coach/consultant who can review how our team currently uses AI, identify opportunities for improvement, and help us work more effectively with Claude Code, agents, and AI-assisted development workflows. What we're looking for: Experience implementing and scaling AI-assisted development practices within agile software teams. Deep hands-on experience with Claude Code, agents, and agent-driven workflows. Experience designing and configuring agents for development, QA, testing, documentation, and other engineering processes. Ability to conduct team workshops, coaching sessions, and practical reviews of our current workflows. Strong understanding of software engineering best practices, not just AI tooling. Bonus skills: Software architecture and platform engineering experience. Experience setting up and optimizing MCPs (Model Context Protocol), tools, integrations, and custom Claude configurations. Knowledge of AI workflows beyond development, including QA, support, project management, and internal operations. The engagement would likely include a mix of: Reviewing our current processes and tooling One-on-one discussions with team members Team coaching and training sessions Recommendations for improving productivity, quality, and collaboration using AI Please include examples of teams you have coached, AI development workflows you have implemented, and your experience with Claude agents and MCP-based tooling

NobleProg is seeking an experienced AI Trainer to deliver a live, instructor-led remote training focused on helping technical professionals integrate Agentic AI and RAG systems into their existing workflows. This opportunity is designed for participants with strong technical backgrounds (Data Engineering and Workflow Automation) but limited formal AI experience, with the goal of applying AI to real-world systems rather than learning theory. Engagement Details Location: Remote Duration: 2 days Audience: Data Engineers and Workflow Developers Participants: 4+ Daily Rate $1,100 per day Course Scope This training focuses on practical, hands-on development of AI-powered systems using Retrieval-Augmented Generation (RAG) and agent-based architectures. The course will follow a Core & Split approach, starting with shared foundational concepts, moving into role-specific deep dives, and concluding with an integrated session demonstrating how AI systems are built and applied across workflows and data pipelines. NobleProg SOP - https://share.synthesia.io/a0788c6e-56d5-4da8-92c6-0d5c03ad6d52 Key Topics Include - Practical introduction to LLM applications and AI system architecture - Retrieval-Augmented Generation (RAG) design and implementation - Data preparation, embeddings, and vector database concepts - Agentic AI fundamentals (tools, decision-making, multi-step workflows) - Orchestration frameworks such as LangChain, LangGraph, or similar - Role-based applications: RAG pipelines for data engineers and AI-driven workflows for workflow developers - End-to-end system integration (RAG + agents + automation) Trainer Responsibilities - Deliver engaging, instructor-led remote training with strong hands-on focus - Translate AI concepts into practical applications for non-AI technical professionals - Structure delivery using a Core & Split model to address different roles - Provide real-world exercises aligned with data pipelines and workflow automation - Facilitate an integrated session demonstrating how different components work together - Prepare training materials (trainer retains ownership of content) Required Qualifications - Hands-on experience building LLM-based applications, including RAG systems and agent-based workflows - Strong proficiency in Python and experience with APIs, data pipelines, or automation systems - Experience with frameworks such as LangChain, LangGraph, or similar - Proven experience delivering technical training to engineering audiences - Ability to simplify AI concepts and connect them to real-world use cases Nice to Have - Background in data engineering, workflow automation, or solutions architecture - Familiarity with MCP or emerging agent orchestration frameworks - Experience designing modular or role-based training programs preferred - Experience building production-grade AI applications preferred https://docs.google.com/document/d/184VlJipyixkLNJ_HnP3aPt4YToedTUAlji_LxkuLhRU/edit?usp=sharing Please review and approve this tentative outline. We will be meeting with the client to determine whether they prefer a 1-day or 2-day delivery format. The agenda may require some adjustments based on the client's specific objectives, technical background, and areas of interest, which can be finalized during the trainer-client consultation call. Could you please review the proposed outline and let us know if you see any red flags, gaps, concerns, or topics that may require immediate attention? We would also appreciate any recommendations regarding scope, level of technical depth, hands-on exercises, or prerequisite knowledge that should be addressed before presenting this to the client. Thank you for your feedback. How to Apply Please include - A brief overview of your experience with Agentic AI and RAG systems - Your experience delivering technical or AI-focused training - Examples of AI systems or applications you have built - Your approach to teaching participants without formal AI background - Availability for remote delivery

# Zapier & AI Automation Specialist for Growing Coffee Catering Company ## Overview Pretty Good Coffee Company is a premium mobile coffee catering company based in Raleigh, NC. We serve corporate events, employee appreciation events, universities, weddings, brand activations, and private events throughout North Carolina. We're looking for an experienced automation specialist to help us build practical systems using Zapier, AI tools, Gmail, and our existing software stack. Our goal is not simply to automate tasks. We want to create systems that improve client experience, increase sales conversion, reduce administrative workload, and help us scale operations without sacrificing hospitality. ## Primary Project: Quote Follow-Up Automation Our highest priority is building an automated quote follow-up system. Current workflow: * Lead submits inquiry * Quote is created and sent through booking platform * Follow-up is currently handled manually Desired workflow: * Detect when a quote is sent * Extract relevant quote details * Use AI (Google AI Studio/Gemini) to generate personalized follow-up emails * Create Gmail drafts (not auto-send) * Trigger additional follow-ups after specific time periods * Maintain a natural, human, hospitality-focused tone We have already begun building this workflow but need an expert to finish and optimize it. ## Future Automation Opportunities After the initial project, we'd like help building additional automations such as: ### Sales * Lead response automation * Quote follow-up sequences * Lead scoring and prioritization * Client re-engagement campaigns * CRM updates and pipeline tracking ### Operations * Automatic event briefs * Staff communication workflows * Event assignment notifications * Calendar and scheduling automations * Inventory forecasting ### Marketing * Review request automation * Testimonial collection * Client nurture campaigns * Social media/content workflows * Monthly reporting dashboards ### Executive Reporting * Weekly business summaries * Lead tracking * Conversion reporting * Revenue dashboards * Operational KPI reporting ## Current Tech Stack * Flashquotes * Zapier * Gmail / Google Workspace * Google AI Studio (Gemini) * Google Sheets * Google Drive Additional platform recommendations are welcome if they simplify operations. ## What We're Looking For * Strong Zapier experience * Experience with AI integrations (Gemini, OpenAI, Claude, etc.) * Experience troubleshooting API and webhook workflows * Ability to think through business processes, not just build automations * Clear communication and documentation * Ability to recommend simpler solutions when appropriate ## To Apply Please include: 1. Examples of similar automation projects you've built. 2. Your approach to quote follow-up and sales automation. 3. Your preferred hourly rate or fixed-price estimate for the initial project. 4. Any recommendations you would make based on the information above. We're looking for a long-term automation partner, not just a one-time freelancer.