We are seeking a highly experienced AI Solutions Architect / AI Agent Developer who has already built production-ready AI agents and can demonstrate previous work. The first engagement will be to provide a live demonstration of AI agents and discuss technical approaches for future client implementations. Successful candidates will become our preferred development partner for future AI projects.Required Experience You must have experience building AI agents using technologies such as: OpenAI APIs Anthropic Claude APIs Retrieval-Augmented Generation (RAG) LangChain or LangGraph Python n8n or Make.com Vector databases MCP (Model Context Protocol) integrations API integrations Microsoft 365 integration SharePoint integration Document automation OCR and PDF processing Database design Secure authentication and authorization Cloud deployment (Azure or AWS preferred)Preferred Experience Experience building AI solutions for: Law firms Construction companies Real estate Logistics and trucking Manufacturing Professional service firms Experience with document generation, contract review, client intake, workflow automation, dashboards, and internal knowledge assistants is highly desirable.Initial Engagement The first phase will include: A live demonstration of AI agents you have already built. Discussion of AI architecture and best practices. Review of our business model. Recommendations for building reusable AI frameworks for our clients. Technical planning for future projects.We value developers who: Think like business consultants, not just programmers. Communicate well with non-technical clients. Care about security and data privacy. Write clean, maintainable code. Can recommend the best technical approach rather than simply taking instructions. Are interested in building a long-term partnership.Please Include With Your Proposal A brief introduction about yourself. Links to AI projects you have built. A short video or live demo of an AI agent (preferred). Your favorite AI technology stack. Your availability. Your hourly rate. Your location and time zone. How many production AI agents you have successfully delivered. Why you believe you would be a good long-term partner.

We are seeking a Claude expert to develop and enhance our AI tool. to integrate all of my marketing using constant contact email and texting. also wanting to integrate all work so I don't have to deal with the mundane. The ideal candidate will have extensive experience with Claude and be able to integrate it into our existing systems. Responsibilities include developing new features, optimizing performance, and ensuring seamless integration with our current infrastructure. The role requires a strong understanding of AI technologies and the ability to work independently.

We are seeking a skilled freelancer to develop a Tavus AI agent capable of interviewing people and recording conversations directly to cloud storage. The ideal candidate will have experience in AI development and cloud integration, ensuring seamless and secure data storage.

We are looking for an experienced mobile app developer to complete a small AI integration task for an existing React Native or Flutter application. Scope of work: * Integrate an AI API (OpenAI, Gemini, Claude, or similar) into an existing mobile application. * Build a simple AI-powered feature based on our requirements. * Ensure the integration is fast, stable, and production-ready. * Deliver clean, well-structured, and documented code. This is a small one-time project. When applying, please include: * 5–10 live mobile apps you've worked on (App Store or Google Play links preferred) * Any AI-powered mobile apps you've built * Your role and contribution to each project * GitHub, portfolio, or LinkedIn profile (if available) Only apply if you have hands-on experience integrating AI into mobile applications.

Need an experienced developer to integrate an AI-powered feature into an existing application. Small scope, fast turnaround

Senior Software Engineer (AI-Focused, Contract – US) Position Summary W Energy is seeking a Senior Software Engineer (Contract) to help drive the integration of AI capabilities into our core platform. This role is focused on building AI-powered product features, not just experimenting with models—embedding intelligence directly into workflows across our upstream and midstream solutions. You’ll design and implement AI-driven functionality that improves automation and user experience. This includes leveraging LLMs, machine learning models, and modern AI tooling within a production SaaS environment. This is a hands-on role for someone who can move quickly, make pragmatic decisions, and bring AI concepts into real, scalable product features. Responsibilities • Design and implement AI-powered features within the platform (e.g., automation, recommendations, copilots) • Integrate LLMs and/or ML models into existing services and workflows • Evaluate, select, and optimize AI tools, APIs, and frameworks for production use • Collaborate with Product to translate business problems into AI-driven solutions • Build and maintain scalable backend services to support AI functionality • Profile, test, and optimize performance of AI-integrated systems • Ensure reliability, security, and cost-efficiency of AI components in production • Contribute to architecture decisions around AI integration and system design • Partner with engineering teams to embed AI into existing applications without degrading stability Requirements • 5+ years of experience as a software engineer in a SaaS or cloud-based environment • Strong backend engineering experience (RoR and/or Golang preferred) • Experience integrating APIs and working within distributed systems • Hands-on experience with AI/ML tools (e.g., OpenAI, Anthropic, Hugging Face, or similar) • Experience building or integrating AI-powered features into applications (not just experimentation) • Strong understanding of data flow, system design, and performance optimization • Experience with relational databases (SQL Server or similar) • Familiarity with microservices architecture, Kubernetes, and CI/CD pipelines • Experience deploying applications in Azure or similar cloud environments • Strong problem-solving skills with ability to work in ambiguous, fast-moving environments • Builder mindset—someone who can take an idea and turn it into a working feature quickly • Pragmatic approach to AI (focus on value, not hype) • Ability to work independently in a contract environment while collaborating closely with internal teams • Strong communication skills and ability to explain AI concepts to non-technical stakeholders Preferred • Experience with prompt engineering, embeddings, or retrieval-augmented generation (RAG) • Exposure to model evaluation, fine-tuning, or AI performance monitoring • Experience with event-driven architectures or real-time data processing • Background in energy, fintech, or other complex data-driven industries

# Full-Stack AI Engineer — Semantic Search + Next.js + Supabase (Long-Term, Contract-to-Hire) ## About We're building an AI-native platform that makes a large archive of recorded talks genuinely discoverable and useful: need-based semantic search over transcribed media, with a subscription product built around it. We have a clear product vision and architecture and are looking for a lead engineer to build the first version and grow with us long-term. Full product details are shared with shortlisted candidates under NDA — this post focuses on the engineering and the skills we need. ## The engineering challenge You'll build a two-part system that shares one database: 1. **A content pipeline (Python):** ingest recorded talks, transcribe them, chunk and enrich the transcripts with metadata using an LLM API, generate embeddings, and store everything in Postgres. 2. **A web app (Next.js):** fast, crawler-friendly, SEO-strong content pages with structured data; retrieval-based search that returns relevant source material with links/citations; user accounts; and Stripe-gated paid content. We care a lot about retrieval *quality* and clean, maintainable architecture — this is a real product, not a prototype. ## Required tech stack - **App:** Next.js (App Router), TypeScript, Vercel. Strong SSR/SSG, SEO, and JSON-LD structured-data experience. - **AI/backend:** Python; production RAG (embeddings, chunking, retrieval quality); LLM API integration. - **Data:** Postgres + **pgvector** (via Supabase); embeddings via a hosted model (Voyage/OpenAI). - **Auth & gating:** Supabase Auth with row-level security. - **Payments:** Stripe (subscriptions + one-time). ## Required skills - Shipped production Next.js (App Router) + TypeScript apps with strong SSR/SEO. - Built a real RAG / vector-search system in production — not a tutorial clone. - Comfortable in Python for data pipelines. - Postgres + pgvector and Supabase in production. - Stripe integration. - Plans before building; communicates clearly in writing. ## Nice to have - Audio/video transcription experience (Whisper / faster-whisper / Deepgram / AssemblyAI). - Agentic coding workflows (e.g., Claude Code). - Content-heavy SEO products or media libraries. ## Engagement - Hourly, contract-to-hire. ~20–40 hrs/week to start; long-term for the right person. - We start finalists on a **small paid test project** (a single self-contained slice of the pipeline) before the full engagement — that's how we evaluate fit. ## Confidentiality This is a proprietary product. Shortlisted candidates sign a mutual NDA before we share full scope and context. Please don't expect complete product details in the first exchange — strong technical applicants will have everything they need to be evaluated, and the rest follows the NDA. ## How to apply Applications that skip these are ignored: 1. **Start your proposal with the word `pgvector`** so we know you read this. 2. Link **two** projects: one live Next.js/SSR app, and one RAG/embeddings or LLM-integration project. Tell us what *you* personally built. 3. Answer briefly: *An offline embedding pipeline and a live search query must use the same embedding model — why does that matter, and how would you guarantee it?* 4. One line on your approach to chunking long-form audio/video transcripts for good retrieval.

Seeking an experienced AI Solutions Architect to provide consultation and design an enterprise-grade Agentic AI platform capable of automating business workflows, retrieving knowledge from enterprise data sources, and integrating with existing business systems. This engagement focuses on solution architecture, technical design, technology selection, implementation planning, and best practices rather than full-scale application development. Scope of Consultation The consultant will: Assess current business processes and identify high-value AI automation opportunities. Design an enterprise Agentic AI architecture aligned with business and technical requirements. Define multi-agent workflows, agent responsibilities, and orchestration strategies. Design a scalable Retrieval-Augmented Generation (RAG) architecture for enterprise knowledge retrieval. Recommend the appropriate Large Language Models (OpenAI, Claude, Gemini, AWS Bedrock, Azure OpenAI, etc.) based on cost, performance, and use cases. Recommend vector database technologies and semantic search architecture. Design secure integrations with enterprise applications, APIs, and internal knowledge repositories. Define prompt engineering strategies, AI guardrails, evaluation methodology, and governance practices. Recommend cloud architecture and deployment strategies for AWS, Azure, or Google Cloud Platform. Provide guidance on LLMOps, monitoring, observability, security, model lifecycle management, and scalability. Develop an implementation roadmap, including phases, estimated effort, risks, and technical recommendations. Required Expertise Enterprise AI Solution Architecture Agentic AI Multi-Agent Systems Retrieval-Augmented Generation (RAG) Large Language Models (LLMs) LangChain LangGraph Prompt Engineering OpenAI API Anthropic Claude Google Gemini AWS Bedrock Python Vector Databases Enterprise System Integration AWS Microsoft Azure Google Cloud Platform AI Governance LLMOps MLOps Workflow Automation Deliverables Enterprise Agentic AI solution architecture document Multi-agent workflow design and orchestration diagrams RAG architecture and knowledge management design Vector database recommendation and data flow architecture Cloud deployment architecture Integration strategy for enterprise systems AI governance, security, and LLMOps recommendations Implementation roadmap with milestones and estimated effort Architecture review presentation and knowledge transfer session Project Outcome Delivered a comprehensive enterprise AI architecture and implementation strategy that provides a scalable foundation for deploying Agentic AI solutions. The consultation enabled stakeholders to make informed technology decisions, reduce implementation risks, accelerate development, and establish best practices for governance, security, and long-term operational success.

Project Capital Advisors (PCA) is seeking an experienced AI Solutions Architect to support a government modernization consulting engagement. The initial project involves helping a county government modernize its citizen telephone operations using Voice AI, workflow automation, and enterprise system integrations. The selected consultant will work directly with executive leadership and public sector stakeholders to assess existing operations, develop technical recommendations, and help define an implementation roadmap. Responsibilities include: * Leading technical discovery sessions with client stakeholders * Evaluating existing phone systems and call workflows * Designing Voice AI and Contact Center AI solution architectures * Recommending enterprise platforms and integration strategies * Creating technical documentation and architecture diagrams * Supporting project scoping, budgeting, and executive presentations Preferred experience: * Enterprise Voice AI or Contact Center AI * Twilio, Amazon Connect, Genesys Cloud, Five9, Retell AI, ElevenLabs, Azure AI, or OpenAI APIs * API integrations and workflow automation * Experience with government or other regulated industries is preferred Engagement Details: * Contract/Fractional * Approximately 10–20 hours per week initially * Remote with occasional travel * Opportunity for additional engagements as PCA expands its Government AI consulting practice Please review the attached position description for complete responsibilities, qualifications, and application requirements.

We're looking for an AI & Data Analysis expert to lead the integration of intelligent tools within the business platform. You'll connect Google Ads, marketing data files, and operational data sources to build AI agents via Claude that support business decision-making across our pet retail operations. Key Responsibilities Design and configure Claude-powered agents using tool use, structured prompts, and automated workflows for data analysis Integrate the Google Ads API to extract campaign metrics and feed decision-making dashboards Ingest, clean, and structure CSV, Excel, and other marketing data formats for agent processing Generate automated narrative reports and actionable visualizations for the executive and marketing teams Maintain and iterate on data pipelines connecting advertising, sales, and inventory data Required Technical Skills Claude API / Anthropic MCP (Model Context Protocol) Prompt engineering and LLM tool use / function calling Google Ads API Python or JavaScript (for pipelines and integrations) SQL / PostgreSQL / Supabase Pandas / NumPy or equivalent data libraries REST API consumption and integration Advanced Excel / Google Sheets Nice to have: Google Analytics, BigQuery, Looker, Power BI Ideal Profile Proven experience building data pipelines or LLM-powered tools in a production environment Hands-on familiarity with the Anthropic API and agent/tool-use patterns Ability to translate raw data into clear, actionable business recommendations Self-directed — can propose and build solutions without exhaustive specs Initial Projects Campaign ROI Agent — connects Google Ads + business sales data to generate automatic performance alerts and recommendations Marketing File Pipeline — ingests CSV/XLSX marketing files and produces AI-generated summaries and insights Executive Dashboard — decision-support interface with Claude-generated action recommendations based on live data