Summary We're an early-stage AI startup building Hirey — an agent-to-agent marketplace that runs inside various AI tools via a plugin. Think "Upwork for AI agents": your agent finds, vets, and books the right human or agent on your behalf. We're looking for 5 AI agent enthusiasts to install our plugin (OpenClaw, Codex, Opus, Gemini), try it out, and sit for a short 10-15 minute video interview about your experience. The interview will be posted on our hirey.ai site. About 45 minutes of your time total. What you'll do Install the Hirey plugin in Codex. It connects your agent to Hirey's remote MCP server, so there's no local server, Node setup, Claude Desktop, or JSON config edit required. Setup is usually: enable the plugin, restart the AI agent you installed on. Connect to Hirey, run a sample workflow, and check out the hirey.ai page. A 10-15 minute video interview with the founding team. We'll ask about your experience with Hirey and your broader take on the AI agent/MCP ecosystem. Camera on, recorded, and published on hirey.ai — by taking part you're agreeing to be filmed and featured on our site. Who we're looking for Someone who has used AI tools in the past, especially for coding or technical tasks. You use Claude Desktop, Cursor, Codex, or similar AI dev tools regularly. Bonus: you've built or contributed to anything in the AI agent / MCP / LangChain / Claude Code ecosystem. What you get $20 flat, released via Upwork on interview completion. A feature on hirey.ai as an early voice in the AI agent space. Early access to the Hirey AI agent network if you want to keep using it. A direct line to the founding team. To apply, answer these in your proposal Have you used an AI coding tool before? Which one(s)? One sentence on a recent AI/agent project you've worked on or played with. Your timezone and earliest availability this week. Confirm you're comfortable being filmed and featured on hirey.ai. We'll respond within 24 hours and schedule interviews within 2 business days. No long applications, no portfolio review. Optimizing for speed.

I’m running a real estate investment platform called ToInvested.com. The project is about 90% finished, and most of the code was built with Claude together with another engineer. Now I need a senior engineer to step in, review the full product carefully, test every major workflow, and help verify that everything is working correctly before it goes live. This is not just a “write more code” role. I need someone who can look at the platform like a real product, find hidden bugs, catch weak logic, test edge cases, review the AI-generated code, and tell me honestly what is ready and what still needs fixing. Because this is a real estate investment platform, accuracy and trust matter a lot. Users may rely on property data, investment logic, calculations, and AI-driven insights, so even small issues can create a serious problem later. The ideal person has strong full-stack experience, understands AI-assisted development, and has a good testing mindset. Real estate tech experience would be a big plus, especially with property platforms, investment tools, marketplaces, mortgage systems, or financial workflows. My main goal is simple: I want someone to break the project before real users do. If you’re the kind of engineer who can take a nearly finished product, test it deeply, clean up weak areas, and help make it production-ready, I’d be happy to talk.

About the Role We're looking for an experienced AI/ML developer to design, build, and deploy production-grade AI systems. You'll work on LLM-powered applications, retrieval-augmented generation (RAG) pipelines, and multi-agent architectures. This is a hands-on role for someone who has shipped real AI products—not just prototypes. Responsibilities Design and implement RAG pipelines (chunking, embeddings, vector stores, retrieval optimization) Build multi-agent systems using LangChain and LangGraph Integrate and fine-tune LLMs (OpenAI, Anthropic, open-source models) Develop and optimize prompts, tool-calling, and agent orchestration logic Deploy scalable, reliable AI services with proper monitoring and evaluation Collaborate on architecture decisions and code reviews Required Skills (Mandatory) Strong AI/ML fundamentals and hands-on experience Proven LLM application development RAG pipeline design and optimization LangChain and LangGraph (production experience) Agent / multi-agent system build experience Vector databases (Pinecone, Weaviate, Chroma, FAISS, or similar) Python (production-level) API integration (OpenAI, Anthropic, Hugging Face) Nice to Have Fine-tuning / LoRA / model optimization Cloud deployment (AWS/GCP/Azure) MLOps and evaluation frameworks (LangSmith, RAGAS) Experience with streaming, caching, and cost optimization

# 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.

Job Title - AI Native Developer Duration - 90 Days Initial Engagement (20 Hours/week) Work Mode- Onsite Work Location- Plano, Tx Position Summary: We are hiring a Senior AI Native Developer to join an active client engagement in the restaurant technology space. This is a hands-on, on-site role with a dual mandate: driving development execution as a Senior Engineer and acting as a client-embedded technical liaison — a Product Owner / Technical Lead hybrid — working alongside the client's CTO, stakeholders, and ISHIR's India-based development team. This role suits someone who thrives in ambiguity, translates business requirements into shipped code, and is equally comfortable presenting to executive stakeholders and writing production-grade AI features in the same week. WHAT YOU'LL DO Client Delivery & On-site Presence Serve as the primary on-site technical SPOC for the client engagement — attend stand-ups, sprint reviews, and stakeholder sessions Represent ISHIR's delivery team with clarity and professionalism; communicate progress, risks, and decisions to CTO and CFO-level stakeholders Facilitate product discovery, requirements refinement, and architecture review sessions on-site Own the client relationship day-to-day, proactively flagging issues before they escalate AI-Native Development Design and build AI-powered product features using LLMs, RAG pipelines, and agentic architectures Integrate AI capabilities — OpenAI, Anthropic Claude, Azure OpenAI — into production web and API systems Write clean, testable, production-grade code across the full stack (frontend through backend through data layer) Own feature delivery end-to-end: from acceptance criteria through deployment and post-go-live monitoring POD Coordination Collaborate daily with ISHIR's India-based developers and QA across time zones via Azure DevOps, Slack, and video standups Translate client decisions and feedback into clear development tasks and backlog items for the offshore team Review pull requests and maintain code quality standards across a distributed team Flag scope changes, technical blockers, and delivery risks to the Program Manager proactively WHAT WE'RE LOOKING FOR Must-Have 8+ years of hands-on software engineering experience, with at least 2 years building AI/ML or LLM-integrated products Proven ability to work directly with clients — comfortable in executive meetings and boardroom-level presentations Strong full-stack background: Python or Node.js backend; React or equivalent frontend Hands-on experience with LLM APIs (OpenAI, Anthropic, Azure OpenAI) — prompt engineering, RAG, tool/function calling Solid agile delivery experience: sprint planning, backlog grooming, coordinating distributed engineering teams US-based with ability to travel on-site to client locations (primarily Dallas, TX area) Exceptional written and verbal communication — you write as clearly as you code Strong Advantages Prior experience in a client-facing technical lead, senior PO, or solutions architect capacity at a services or consulting firm Familiarity with restaurant technology, hospitality SaaS, or B2B platform products Experience with Azure DevOps, CI/CD pipelines, and cloud-native deployments (Azure preferred) Hands-on with agentic AI frameworks — LangChain, LangGraph, AutoGen, or similar Anthropic Claude Certified Architect (CCA-F) or equivalent AI platform certification ABOUT ISHIR ISHIR is a digital innovation and enterprise AI services provider. We work with startups and enterprises to shape the future through accelerated innovation, deep technical expertise, access to global digital talent and a passion for complex problem-solving. With our help, our clients overcome their most difficult digital challenges leveraging AI. We are not just consultants, we are partners in our clients’ success, assisting them with re(gaining) competitive edge by identifying opportunities for differentiation, industry disruption, scalable innovation, and go-to-market strategies that deliver successful outcomes. At ISHIR, we help bold businesses accelerate innovation through Talent, Speed-to-Market, and AI. We help make an impact by solving real problems using innovation, improved customer experiences and the right technologies. As an ISHIR employee, you will get the advanced training you need to be successful, and the opportunity to apply it. You must be passionate about technology, crave responsibility, and be eager to apply your knowledge to real business solutions for our startup and enterprise customers. These are the qualities of a person destined for success at ISHIR. ISHIR attracts a special type of individual—someone who is proactive, thrives on challenges, feeds off success, and looks at moving targets not as obstacles but as opportunities. ISHIR is an exciting place to work. It is imbued with an entrepreneurial spirit and promotes self-reliance, open communication, and collaboration

We are an investment firm with a portfolio of healthcare companies. We are seeking to begin building our data capture systems across our business and layer AI to surface summarize and store insights. This is a process that is in parallel to our operations team SOP'ing our process in anticipation of expansion. It is our opinion that we have a relatively simple business process from end to end and lots of potential to capture useful data signals across each department/function. We have drafted a rough business process / data ontology diagram showing our preferred approach. We are seeking an expert to: 1 ) Create lightweight data systems to capture data signals from end to end across our business (Recruiting to Onboarding to Scheduling to Payroll to Finance to Legal to). This also includes organizing and categorizing our past / existing data in addition to capturing signals for future data. 2 ) Layer AI / agentic AI automations that can surface insights, categorize and aggregate info, populate knowledge databases, etc. Example Data Signals / Use Cases: Fireflies recorded meetings Tagging emails in inbox as Legal/Finance/Scheduling/Onboarding etc Job Board Postings Airtable (For building a lightweight scheduling/employee management system) (For storing a knowledge database and rolodex) To Apply: Please briefly present an instance of implementing a similar lightweight solution to capture data signals and convert the data into meaningful and actionable insight via AI

Are you an experienced web developer who loves building applications, enjoys mentoring, and is excited about leveraging AI to code faster? I am looking for a sharp, collaborative technical partner to work with me live over Zoom to build out various web applications. A core part of our workflow will involve utilizing Claude (and other AI tools) to brainstorm, scaffold, and accelerate our development process. Instead of working in isolation, you will be partnering with me in real-time to solve problems, review code, architect solutions, and push projects across the finish line. What You’ll Do Live Pair Programming: Join scheduled Zoom calls to actively write, debug, and review code together. AI Collaboration: Work alongside me to prompt, refine, and implement code generated by Claude to speed up the development lifecycle. Web Application Development: Help build, test, and deploy functional, clean web applications from scratch or improve existing codebases. Architectural Guidance: Offer advice on best practices, database design, and framework selection based on project needs. What I’m Looking For Strong Technical Foundations: Proficiency in modern web development frameworks and languages (e.g., JavaScript/TypeScript, React, Node.js, Python, or similar modern stacks). AI-Fluent: You don't just know how to code; you know how to use AI tools like Claude efficiently to debug, generate ideas, and optimize workflows. Excellent Communication & Patience: Since we will be working live on Zoom, you must be a clear communicator who enjoys explaining technical concepts and brainstorming out loud. Problem Solver: A knack for breaking down complex feature requests into manageable, step-by-step development tasks.

Looking for an experienced AI propter to use tool of their choice to re-organize a chart in the page below to the following parameters- the remainder of the page to be left alone: Group all clergy by diocese Put in a bulleted list format Remove the last name / first name boxes Re-write the description of the offense to include more information- but keeping concise Make the revision not detectable to AI filters here is an example of a page to be reivised: https://www.injurylawyerteam.com/blog/michigan-catholic-diocese-priest-sex-abuse-list/ there are more if we can fit a good template

The Client seeks an experienced AI development team to design and build a secure web-based document intelligence platform capable of analyzing multiple related documents, extracting key information, identifying inconsistencies, and generating issue reports. The platform will support complex document sets where information must remain consistent across multiple files and versions. The initial scope focuses on document ingestion, data extraction, cross-document analysis, issue identification, and reporting. Business Objective Develop a scalable SaaS application that enables users to: • Upload and organize multiple related documents • Extract key terms, dates, parties, financial values, and references • Compare information across documents • Identify inconsistencies and missing information • Generate issue reports and review summaries • Maintain document version history • Provide an intuitive dashboard for issue management Phase 1 – Document Ingestion and Processing Requirements Develop a secure document upload module supporting: • PDF • Microsoft Word (.docx) • Microsoft Excel (.xlsx) • Text files System shall: • Extract text from uploaded files • Preserve document structure • Capture headings and section hierarchy • Process tables and schedules • Index document content for search and retrieval Phase 2 – Data Extraction Engine The platform shall automatically identify and extract: • Defined terms • Parties and entities • Dates • Numerical values • References to exhibits and schedules • Section references • Key metadata Extracted information shall be stored in a searchable database. Phase 3 – Cross-Document Consistency Review The platform shall compare extracted information across multiple documents and identify: • Inconsistent terminology • Conflicting dates • Conflicting numerical values • Missing references • Undefined terms • Duplicate provisions • Broken cross-references Examples include: • Same entity referenced using multiple names • Different numerical values for the same item • References to sections that do not exist • Missing exhibits or attachments Phase 4 – AI Review and Issue Identification The platform shall integrate a Large Language Model (LLM) to perform contextual analysis. The AI engine shall: • Summarize document contents • Identify potential drafting inconsistencies • Highlight missing information • Generate issue descriptions • Assign issue severity levels • Provide suggested corrective actions Phase 5 – Dashboard and Reporting Develop a web-based dashboard including: Transaction Workspace • Document list • Upload history • Processing status • Review status Issue Tracker • Issue category • Issue severity • Source document • Description • Resolution status Search Functionality Search by: • Term • Date • Party • Numerical value • Document name Reporting Generate downloadable reports in PDF and Excel format. Technical Requirements Frontend • React or Next.js Backend • Python • FastAPI preferred Database • PostgreSQL Vector Database • Pinecone, Weaviate, or Chroma AI Integration • OpenAI API • Anthropic API • Retrieval-Augmented Generation (RAG) architecture preferred Security Requirements • User authentication • Role-based permissions • Encrypted document storage • Audit logging • Secure API access Deliverables Functional web application Source code repository Database schema API documentation Deployment documentation Administrator guide User guide Ownership and Intellectual Property All work product, source code, documentation, specifications, workflows, business logic, prompts, training materials, and derivative works developed under this project shall be deemed works made for hire and shall be the sole and exclusive property of the Client. Contractor shall assign all intellectual property rights to the Client upon creation. Contractor shall not reuse, disclose, distribute, or commercialize any portion of the work product without the Client’s prior written consent.

Join our team as a senior AI Architect working closely with our product and engineer teams to design practical AI capabilities within our SaaS platform. This is a hands-on role focused on building reliable, production-grade conversational and AI-assisted features — not experimental research projects. You will work closely with product and engineering teams to design scalable AI patterns, integrate modern LLM technologies, and help shape how AI capabilities are embedded into real operational workflows. You will focus deeply on architecture, implementation quality, reliability, usability, scalability, observability, and operational robustness. This role is ideal for someone who understands both modern AI tooling and the realities of shipping enterprise SaaS software in production environments. We value people who can think critically about architecture, tradeoffs, operational realities, and long-term maintainability — not just prototype AI demos.