We are a small residential real estate investment company seeking an AI Solutions Architect to enhance our acquisition platform. The role involves designing and implementing AI solutions to improve data analysis and decision-making processes. The ideal candidate will have experience in AI architecture and a strong understanding of real estate data analysis.

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.

We're building an internal operations platform to automate utility account management for a large real estate portfolio. Today, much of this work is manual. Information about utility accounts exists across multiple systems, and employees spend significant time identifying missing bills, reconciling account data, researching exceptions, and coordinating follow-up work. We're building a system that automates these processes by synchronizing data between our operational system and accounting system, applying business rules to identify exceptions, and presenting actionable work queues and dashboards for our operations team. Examples include: Utility accounts that exist in one system but not another Missing or delayed utility bills Accounts requiring setup or closure based on occupancy changes Autopay and e-bill tracking Operational exceptions that require human review Dashboards, work queues, assignments, notes, and status tracking Our internal product manager owns the business requirements and workflows. Your role is to work closely with them to design and implement the technical solution, not to perform business process discovery. What You'll Do Design and use AI to build the application's backend and frontend. Design a clean, maintainable application architecture. Use AI to build dashboards and workflows that allow operations teams to efficiently manage exceptions. Translate product requirements into production-ready software. Leverage AI development tools (Codex, Claude Code, Cursor, or similar) as a core part of your workflow to accelerate development. Review, validate, and refine AI-generated code to ensure quality and maintainability. What We're Looking For We're looking for an experienced software engineer with strong software engineering fundamentals who embraces AI-assisted development. You should understand how modern software applications are architected, designed, built, and deployed, and be comfortable making sound technical decisions while moving quickly. Experience in many of the following areas is preferred: Full-stack application development Application architecture and system design APIs and system integrations SQL databases and data modeling Authentication and security Cloud-hosted applications Testing and debugging Source control and collaborative development We care much more about engineering judgment, speed of execution, and the ability to effectively leverage AI than expertise in any particular language or framework. Nice to Have Experience building internal business applications or operations platforms Experience working with accounting, ERP, or workflow systems Experience building dashboards and operational tooling To Apply Please include: A brief summary of your experience building business applications. The AI development tools you use regularly (Codex, Claude Code, Cursor, Windsurf, etc.) and how they fit into your workflow. Examples of projects where AI significantly accelerated your development process. Your availability over the next 2–3 months and your expected hourly rate.

We are seeking an experienced AI workflow / operations consultant to help us build repeatable “business of the future” blueprints for niche service industries. We are not building a new AI product. We want help identifying the best existing tools, workflows, and automation opportunities to modernize service businesses in a practical, scalable way. We want someone who can help us: map current workflows identify the best opportunities for AI and automation recommend the right tool stack define what should stay human vs. what should be automated create standardized implementation blueprints we can deploy across multiple clients We are looking for someone with real operational depth, not just generic AI enthusiasm. Bonus if you have worked in: healthcare legal compliance-sensitive service businesses CRM / automation / intake / communication systems Please send examples of similar work and explain how you would approach building a scalable modernization blueprint for these kinds of businesses.

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.

Overview We're building an open-source CLI gateway for multi-agent AI orchestration — model-agnostic, MCP-native, and designed to bring any agent framework online with a single command. The repo is active, well-documented, and growing. We need an engineer to accelerate integration coverage and help attract open-source contributors. The Work Build agent templates and runnable examples for LangGraph, CrewAI, and similar frameworks Add LLM provider support (Groq, Mistral, Gemini, etc.) to the Hermes runtime Write clean, contributor-friendly code that models good PR hygiene Submit work via fork → PR → merge workflow on GitHub You Are Strong Python developer with CLI tooling experience Familiar with at least one of: LangGraph, CrewAI, LiteLLM, LangChain Comfortable with open source GitHub workflows (fork, PR, issues, reviews) Self-directed — you read docs, ask good questions, and don't wait to be unblocked Nice to Have Experience with MCP (Model Context Protocol) Familiarity with SSE, OAuth 2.1, or agent credential management Prior open source contributions Engagement Part-time to start, 20 hrs/week Fixed milestones per integration delivered Potential to grow with the project To Apply Share your GitHub profile and one example of open source work or a project that shows your Python and agent framework experience. https://github.com/ax-platform/ax-gateway

I am looking for an experienced ASR engineer to build a production-ready speech-to-text system for a low-resource language. I already have approximately 3,000 prepared audio segments, totaling about 10 hours of audio, with clean and consistent transcripts ready for immediate use. Data preparation and segmentation are already handled. The initial 10 hours of audio will serve as the first milestone. After that, the engineer will be expected to continue training and improving the model with additional data until the system reaches a target WER of 10% or below. Your responsibility will focus on: Fine-tuning a Whisper-based model for high transcription accuracy Optimizing word error rate (WER) over time Providing inline/embedded start timestamps per phrase Building an efficient inference pipeline for both real-time and batch transcription Structuring evaluation and improvement workflows Preparing the system for deployment and integration into a web platform Providing clear documentation and guidance so I can independently continue training and improving the model over time without ongoing engineer involvement The goal is to reach strong accuracy at launch, with a clear process for continued improvement as more data becomes available. Please describe your experience with Whisper fine-tuning or similar ASR model training in your proposal.

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

Looking for a skilled full-stack developer to help build and refine an early-stage SaaS platform currently in MVP development. The platform combines guided workflows, AI-assisted functionality, user dashboards, and subscription-based features within a modern web application experience. We're looking for someone who can help transform an existing concept and partial prototype into a polished, scalable product. Ideal for developers interested in: SaaS platforms AI integrations Scalable web applications Subscription products Startup environments Responsibilities: Frontend and backend development Authentication and user dashboards Stripe/payment integration Database architecture API integrations Responsive UI/UX refinement Scalable application structure Deployment and production setup Preferred Stack: React / Next.js Node.js PostgreSQL Tailwind CSS Stripe REST APIs OpenAI or similar AI integrations Ideal Candidate: Strong full-stack development experience Experience building SaaS products Comfortable working independently Understands scalable architecture Good communication skills Startup mindset Bonus: Experience with AI-powered applications Experience with multilingual platforms Project Stage: Early-stage MVP Potential long-term collaboration Please send: Portfolio or GitHub Relevant projects Preferred stack Hourly rate or project estimate Availability

We are seeking an AI Automation Implementation Expert to enhance our business processes. The ideal candidate will have experience in implementing AI solutions to improve efficiency and productivity. Responsibilities include analyzing current systems, identifying areas for automation, and implementing AI-driven solutions. The candidate should be able to work independently and provide insights on AI best practices.