We're hiring 2 experienced developers to build AIOS deployments for our growing client base. FluentOS is a 9-person team that builds AIOS (AI operating systems) that connect a business's existing platforms together and run AI agents on top of them. We're onboarding 6–7 new client projects every week and need two more builders who can take a project and deliver it. The industries we work in: We deploy across a wide range of professional and service businesses, so you'll get variety: - Financial services & wealth advisory - Tax & accounting firms - Dental and medical practices - Home services & roofing - Property management Each client runs on a different stack — CRMs, comms tools, scheduling, payment systems, document and data sources — and our job is to unify those into one system and build agents that operate across them (lead response, follow-up, reporting, document workflows, estimating, intake, and more). What you'd be building: - AIOS deployments end to end — integrating client platforms via their APIs - AI agents that read/write across those connected systems - Reliable, production-grade automations that real businesses depend on daily What we're looking for: - Proven delivery experience — you've shipped projects clients actually use, not just personal experiments - Strong coding background (Python and/or TypeScript); comfortable with API integrations and agent frameworks - Experience with LLM/agent development (Anthropic/Claude, tool use, multi-step agents) is a big plus - Fast, organized, and communicative — we move quickly and build as a team, not in isolation - Able to work closely with Ray, our lead developer, who'll get you ramped into live projects The setup: - 1099 contract, paid per project — not salaried - Steady, scalable volume (6–7 new projects/week) means consistent work for builders who deliver - Strong potential for ongoing, long-term collaboration as we scale To apply: Tell us briefly about a real project you've built and delivered — ideally something involving API integrations, automation, or AI agents. Include links to work or repos if you have them. Please start your reply with the word "FLUENT" so we know you read this. We'll be scheduling interviews shortly.

I need an expert senior software engineer that can provide consulting services around implementation best practices of LLM's and AI into existing application workflows. i.e. leveraging AI to extract data from a document as part of an ingestion pipeline.

We are looking for 2-3 AI engineers/developers to help us build/complete an AI go-to-market (GTM) tool that looks at both structured and unstructured data, runs it all through our AI engine, and provides insights and recommendations straight to sales people. The tool is able to handle large volumes of data and provide actionable insights for business decision-making. Our engine consists of a prioritization algorithm, pattern matching and sentiment analysis. We use our recommendation engine to deliver the output (insights) straight to our tool which is "Apple-simple", intuitive and gamified. No more sales time wasted on looking at dashboards and trying to agree on which insights are important and which should be acted on. What you'll do Own features end-to-end across theFastAPI backend (IEngine) and Next.js 15 / React 19 frontend— from Claude prompt design to UI polish. Extend the intelligence pipeline: meeting ingestion (Google Drive + Deepgram realtime), Claude-driven action card generation, Neo4j relationship graph, and Supabase-backed state. Build customer-facing dashboard surfaces — deals, gamification, coaching, trust graph — with TypeScript, Tailwind, shadcn/ui, and D3. Operate WebSocket transcription sessions and async job pipelines reliably under real meeting load. Instrument with Sentry, harden auth (NextAuth :left_right_arrow: JWT :left_right_arrow: FastAPI service-to-service), and keep deploy pipelines green. Build with simulators: when you can't test against live meetings, generate realistic synthetic transcripts through our simulator service. Stack you'll work in Backend: Python 3.11, FastAPI, Uvicorn, PyJWT, Anthropic SDK, Deepgram, Neo4j, Supabase (Postgres + realtime), WebSockets Frontend: TypeScript, Next.js 15 (App Router), React 19, NextAuth 5, Tailwind, shadcn/ui, D3, Stripe Infra: Fly.io, GitHub Actions, Sentry, Supabase AI: Claude (Opus/Sonnet) for transcript analysis, action card generation, and agentic dev workflows What we're looking for 4+ years building production web applications, ideally across Python and TypeScript. Comfort designing and shipping features against an LLM API — prompt iteration, structured outputs, evals, cost/latency tradeoffs. Real Claude or OpenAI production experience required. Experience with multi-tenant SaaS patterns, JWT auth, and one or more of: graph databases, realtime systems, audio/transcription pipelines. Comfort with AI-assisted development workflows (Claude Code, Cursor, etc.) — not just as a code-completion tool, but as a way to plan and ship features. Bias toward shipping. Small surface area, high ownership, no committee.

Overview Transit & Flow is a fast-scaling Columbus home services company (plumbing, HVAC, drain, sewer, water heater, sump pump) building a premium, AI-powered operation. We are wiring together a set of best-in-class platforms into one self-functioning system that captures, books, reschedules, reminds, invoices, and follows up with customers automatically across phone, website chat, and Thumbtack. We need a senior integration specialist to stand this up cleanly, end to end, on a short-term contract. This is an execution role for someone who has built production voice-AI and automation systems before, not a learner. Detailed architecture blueprints will be provided to the hired contractor under NDA. What you will build A connected stack with no manual re-entry between systems: • Bland AI voice agents (several agents: inbound scheduler, after-hours and emergency handling, Thumbtack lead agent, and an outbound reminders and follow-up agent) • A website chat agent running the same booking logic in text • Thumbtack Live Connect bridged to a Bland agent via API and webhook, plus the Thumbtack lead feed into our automation bus • Quo.com as the telephony and SMS layer (call forwarding to Bland, SMS send via API, one consistent business number) • GoHighLevel CRM integration (contact sync, pipelines, nurture) • Make.com as the orchestration layer (scenarios for booking, rescheduling, reminders, estimates, invoicing, lead intake, error handling) • Scheduling, rescheduling, cancellation, and automated appointment reminders against our field service management platform (currently Jobber, migrating to OctopusPro, so platform-flexible API work is required) • Email automation including emailing and resending invoices and receipts on request Core responsibilities • Configure Bland pathways, custom tools, and webhooks that read and write to our systems mid-call (check availability, book, reschedule, cancel) • Build robust Make.com scenarios with idempotency, retries, error handling, and alerting • Integrate REST APIs and webhooks across Bland, Quo, GoHighLevel, Thumbtack, the FSM, and email • Bridge Thumbtack Live Connect to a dedicated Bland number so leads are answered live • Implement automated SMS and voice reminders with confirm and reschedule handling • Document everything and deliver a clean handoff so the system is maintainable and scalable Must-have skills • Proven production experience with a voice-AI platform: Bland strongly preferred, or Vapi, Retell, or Synthflow with transferable skill • Advanced Make.com (or n8n) including webhooks, data stores, error handling, and routing • Strong REST API and webhook integration skills, JSON, authentication, signing • GoHighLevel API experience • Telephony and SMS concepts: call forwarding, SIP or number routing, A2P • Ability to design for scale and reliability, not just a demo that works once Nice to have • Quo.com or comparable VoIP platform experience • Thumbtack pro tooling or lead-response automation experience • Home services or field service management background • OctopusPro, Jobber, or similar FSM API experience Engagement • Short-term contract, estimated 3 to 5 weeks • Milestone-based fixed price preferred, hourly considered for the right expert • Async daily updates, a few live working sessions per week • NDA and scoped system access required; you will not receive owner credentials How to apply Do not send a generic proposal. Answer these in your application: 1. Link or describe a voice-AI agent you built that booked or scheduled against a live external API mid-call. What platform, what API, what was the hardest part? 2. How do you make Make.com or n8n scenarios idempotent and resilient to duplicate webhooks and failed calls? 3. In two or three sentences, how would you bridge Thumbtack Live Connect to a voice AI agent so the agent answers the lead live? 4. Your proposed milestone breakdown and realistic timeline for the scope above. 5. How you handle client credentials and secrets securely. Strong applications that show real systems thinking move to a short paid test task before the full award.

We’re looking for experienced AI professionals to provide short, original quotes, practical insights, and light content feedback for our educational articles and guides. Your real-world perspective will help make the content more accurate, useful, and trustworthy for readers. The initial project involves reviewing and contributing to one guide, with the possibility of ongoing work. Example guide: onlinemastersdegrees.org/best-programs/information-systems/ **What You’ll Do:** * Review AI education content for accuracy and clarity * Leave light feedback through Google Docs comments * Provide brief expert quotes, usually 2–5 sentences each * Offer practical insights based on real-world AI, machine learning, or data science experience * Help add context around AI careers, degree programs, certifications, skills, tools, and industry expectations **For the Initial Project:** We’re looking to add approximately 3–4 short expert quotes to one AI guide. Quotes should be original, practical, and based on your professional experience. **Details:** * $30 per page * Pages typically take 20–30 minutes * Clear guidelines and examples provided * Contract, flexible, and ongoing work **Relevant Experience May Include:** * Artificial intelligence * Machine learning * Data science * Generative AI * Natural language processing * Computer vision * AI product development * MLOps * AI governance, risk, or compliance * Responsible AI * AI education or workforce development **In your submission, please include:** 1. A few sentences about your AI background, professional experience, and areas of expertise 2. Any relevant degrees, certifications, credentials, or notable AI projects 3. Link to your LinkedIn profile To help us sort through automated submissions, please put the name of Shopify’s CEO at the top of your submission.

I am a Ph.D. and digital product business owner who uses AI (Claude, ChatGPT, and other AI tools) every day to build, market, and scale my business. My 12-year-old son and I are looking for an experienced AI tutor who can teach us how to work with AI effectively—not just how to ask questions, but how to think, build, create, and solve problems with AI. This is an ongoing coaching relationship, not a one-time class. I already use AI daily and want to become significantly more advanced in prompt engineering, AI workflows, automation, and business applications. My son is curious, creative, and highly motivated. We want someone who can grow with him over the coming years as AI continues to evolve. WHAT WE ARE LOOKING FOR • Weekly one-on-one coaching sessions (one for me, one for my son) • Hands-on learning using real projects—not lectures or slide presentations • Practical skills that can be used immediately • A structured curriculum that builds over time • Someone who enjoys teaching and can explain complex ideas clearly • Experience with Claude, ChatGPT, and current AI tools MY LEARNING GOALS I use AI every day and want to continue improving how I work with it. Topics include: • Advanced prompt engineering • AI workflow design • Prompt refinement and iteration • Research and fact-checking • Marketing copy • Product descriptions • Sales pages • Email sequences • Business automation • AI-assisted content creation • Website content • Productivity systems • Emerging AI tools and best practices JORDAN'S LEARNING GOALS Jordan is 12 years old. While we'll certainly use AI for school projects and writing, our larger goal is to help him develop future-ready skills that will grow with him through middle school, high school, college, and beyond. We are looking for someone who can progressively teach him how to use AI to create, build, and solve problems. Topics may include: • Learning how to communicate effectively with AI and using AI to support academic success • Critical thinking and verifying AI responses • Research and creative writing • Brainstorming and problem solving • Website design and development with AI • Creating simple games with AI • Building apps and digital tools as his skills grow • Learning basic programming concepts using AI as a coach • Entrepreneurship and business ideas • Using AI to help businesses become more efficient • Marketing and content creation • Responsible and ethical use of AI • Developing confidence as a creator—not just a consumer—of AI technology The ideal tutor enjoys helping young people build real-world skills and can gradually increase the difficulty as Jordan grows. WHAT WE ARE LOOKING FOR IN YOU • Demonstrated experience teaching AI—not simply using it • Strong prompt engineering knowledge • Comfortable teaching both an adult professional and a motivated 12-year-old • Patient, engaging, and adaptable • Able to build a long-term curriculum instead of isolated lessons • Reliable, organized, and an excellent communicator Bonus experience: • Programming or software development • Website development • AI-assisted coding • Game development • Digital marketing • Entrepreneurship • Small business consulting LOGISTICS • Two weekly sessions (one for Jordan and one for me--45–60 minutes each) • Zoom • Weekly to start • Start date: ASAP • Budget: Please include your hourly rate. TO APPLY Please include: Your hourly rate. Your experience teaching AI and prompt engineering. An example of how you would structure Jordan's first month of lessons. An example of how you would structure my first month of lessons. What you think will be the most valuable AI skills for a motivated 12-year-old to develop over the next five years. Applications that do not answer these questions will not be considered. We are looking for someone who enjoys teaching, stays current with AI, and is excited about helping both a business owner and a young learner become confident, capable AI users and creators.

26ers is building Human + AI operating systems that help organizations improve decision quality, execution speed, and organizational leverage. We are seeking a customer-facing AI Architect who can work directly with executives, operational leaders, and technical teams to design practical AI solutions that solve real business problems. This role helps organizations identify high-value AI opportunities, redesign workflows, modernize operations, and implement Human + AI operating systems that improve execution, decision-making, and organizational effectiveness. The ideal candidate can move fluidly between customer conversations, workflow discovery, solution design, governance considerations, and implementation planning. Responsibilities • Participate in customer discovery and solution design conversations • Analyze current-state workflows and identify AI transformation opportunities • Design Human + AI operating models, agentic workflows, and operational systems that improve execution and decision-making • Create solution blueprints, implementation plans, and statements of work • Collaborate with implementation developers and technical delivery teams • Consider data governance, security, compliance, and operational requirements throughout solution design • Contribute to the development of reusable 26ers methodologies, frameworks, and institutional knowledge • Design systems that capture, structure, and operationalize organizational knowledge and institutional learning Ideal Experience • Experience designing AI-powered business workflows and operational systems • Strong understanding of OpenAI, Claude, and modern LLM-based solution design • Experience with workflow orchestration platforms, AI agents, automation systems, and API-based architectures • Strong understanding of data governance, information security, and enterprise AI deployment considerations • Experience translating business requirements into solution architectures, implementation plans, and statements of work • Customer-facing experience in consulting, solution engineering, professional services, digital transformation, or technical advisory roles • Experience conducting discovery workshops, workflow assessments, and current-state/future-state design exercises • Understanding of operating model design, workflow modernization, and organizational transformation • Strong written and verbal communication skills with executive stakeholders • Ability to leverage AI tools to rapidly produce architecture drafts, blueprints, requirements documents, implementation plans, training materials, and customer deliverables Nice to Have • Experience with Gemini, MCP, LangGraph, CrewAI, AutoGen, or similar orchestration frameworks • Experience with n8n, Make, Zapier, or workflow automation platforms • Experience with vector databases, RAG architectures, and organizational knowledge systems • Experience building or deploying multi-agent systems • Government, healthcare, financial services, or other regulated industry experience • Startup, founder, or early-stage company experience • Experience designing systems that capture institutional knowledge, operational learning, or organizational intelligence • Military, consulting, enterprise software, or transformation leadership experience Success in this role • Quickly understand a client's operating environment, workflows, and business objectives • Identify high-value opportunities for AI-enabled transformation and operational leverage • Translate customer goals into practical solution designs, implementation plans, and delivery roadmaps • Balance innovation, governance, security, and operational realities • Help organizations move from AI experimentation to operational execution This role may begin on a contract basis and expand into a longer-term strategic partnership as 26ers grows.

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

We are looking for a senior, enterprise-grade Software Engineer to build a high-performance Proof of Concept (POC) for an Autonomous B2B Insurance Compliance & Asset Monitoring Agent. The system will bridge the gap between complex commercial insurance policy guidelines (unstructured data via RAG) and real-time operational telemetry (structured IoT log streams in Snowflake). The goal is an intelligent agent that dynamically analyzes asset anomalies against policy definitions to flag compliance breaches instantly. This is a highly intensive 1-week, 50-hour sprint for an engineer who understands complex data schemas, time-series IoT data gravity, and deterministic agent routing. Core Architecture Requirements (What You Will Build) The Multi-Agent Orchestration Layer: Build an autonomous agent framework (using LangGraph, AutoGen, or native Python execution loops) capable of multi-step reasoning, tool-calling, and error self-correction. Snowflake & IoT Data Lake Integration: Grant the agent secure access to a Snowflake environment containing structured IoT asset monitoring data (e.g., machine telematics, temperature logs, usage hours, maintenance schedules). The agent must dynamically discover schemas and write optimized SQL queries to aggregate this data. Insurance Compliance Hybrid RAG Pipeline: Implement a semantic search architecture to parse and embed dense, unstructured insurance underwriting guidelines, warranty contracts, and B2B compliance policies into a vector store. Deterministic Tool Use & Evaluation: The agent must safely look up a specific policy compliance rule (via RAG) and then automatically generate and execute a targeted query against the Snowflake IoT data lake to verify if real-world asset telemetry violates that specific rule. Required Technical Stack & Expertise Languages & Core Frameworks: Python (FastAPI / Typer), LangChain / LangGraph, LlamaIndex. AI & Embeddings: OpenAI GPT-4o / Anthropic Claude 3.5 Sonnet APIs, vector databases (Pinecone, pgvector, or Snowflake Cortex search). Data Architecture: Deep production experience with Snowflake, cloud data lakes, time-series IoT data manipulation, and advanced text-to-SQL generation patterns. Observability: Implementation of tracing tools like LangSmith, Phoenix, or Arize to monitor prompt tokens, routing paths, and costs. Project Timeline & Deliverables (50 Hours) Phase 1 (Hours 1–15): Environment setup, ingestion of sample insurance policy PDFs into the vector store, and secure connection string setup to a Snowflake mock IoT dataset. Phase 2 (Hours 16–35): Core development of the multi-agent execution loop, prompt tuning for text-to-SQL generation against time-series data, and policy-to-telemetry mapping logic. Phase 3 (Hours 36–50): Observability integration, edge-case testing for hallucination mitigation (ensuring false compliance flags are eliminated), clean code delivery, and a walkthrough video demonstration. If this sprint goes smoothly, there is an immediate opportunity to extend this contract into long-term architecture maintenance, production scaling, and integration into our core platform. Please include real examples of multi-agent, IoT, or insurtech data pipelines you have personally built in your application.

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