We're hiring a senior AI developer to build and deploy AI solutions for a fintech/credit-union platform. The work spans autonomous banking agents, fraud detection, credit scoring, and bill-pay/invoice automation — at the intersection of LLMs, cloud infrastructure, and financial-domain expertise, with security and compliance built in from the start. This is a long-term, ongoing engagement. What you'll do: AI agents & orchestration - Design, build, and deploy multi-agent systems using Amazon Bedrock Agents, LangChain, and related frameworks - Architect agentic workflows for core banking use cases: credit scoring, fraud detection, bill-pay automation, invoice management - Define agent personas, memory strategies, tool-use patterns, and escalation paths for production banking agents LLM engineering - Fine-tune, prompt-engineer, and evaluate LLMs for financial-domain tasks - Build RAG pipelines over credit-union knowledge bases, policy docs, and member data - Implement guardrails, content filtering, and compliance checks for safe, regulated outputs - Monitor performance, hallucination rates, and latency against SLAs Cloud infrastructure (AWS & Azure) - Architect and manage AI/ML workloads on AWS (Bedrock, SageMaker, Lambda, S3, IAM, VPC) and Azure (OpenAI Service, Azure ML, AKS) - Design secure, cost-optimized environments compliant with NCUA, PCI-DSS, and SOC 2 - Implement infrastructure-as-code with Terraform or AWS CDK DevOps & MLOps - Build and maintain CI/CD pipelines (GitHub Actions, Jenkins, CodePipeline, Azure DevOps) - Containerize services with Docker, orchestrate with Kubernetes (EKS/AKS) - Apply MLOps best practices: model versioning, A/B testing, canary deployments, automated rollback - Stand up observability with logging, tracing, and alerting Python development - Write clean, well-tested Python for AI pipelines, REST APIs, and data workflows - Build FastAPI/Flask microservices exposing agent capabilities to frontend and core banking systems - Integrate with financial data sources, core banking APIs, and third-party fintech services Banking applications - Build credit-scoring models using alternative data and explainable AI (XAI) - Develop real-time fraud detection with behavioral analytics, anomaly detection, and auto-decisioning - Create conversational agents for bill pay, account management, and member self-service - Automate invoice workflows: extraction, classification, approval routing, reconciliation - Partner with compliance/risk to keep AI decisions auditable, fair, and regulatory-compliant What you should have: - 5+ years software engineering; 3+ years in AI/ML or LLM engineering - 2+ years building AI for banking, credit unions, or financial services - Hands-on experience with Amazon Bedrock, LangChain, Python, AWS, and infrastructure-as-code - Working knowledge of NCUA, PCI-DSS, SOC 2, GLBA, and Fair Lending requirements - Bachelor's or Master's in Computer Science, Software Engineering, Data Science, or related field Nice to have: - AWS or Azure AI/ML certifications - Open-source LLM experience (Llama, Mistral, Phi) and self-hosted inference (vLLM, Ollama) - Vector databases (Pinecone, OpenSearch, pgvector) - Graph-based fraud networks and graph ML - AI governance / responsible AI framework experience - Prior work at a credit union, community bank, or fintech lending platform To apply, please share: - Your resume highlighting AI and banking project experience - A brief note on your most impactful AI agent or LLM project in a financial-services context - Links to GitHub, portfolio, or published papers (optional but encouraged)

AI Developer Needed – Build Us a Marketing AI Agent We need a skilled developer to build an AI-powered Marketing Assistant for our business. **Core Tasks the Agent Will Handle:** - Appointment setting & lead qualification - Copywriting (emails, ads, social content) - Automated follow-up sequences - Lead research and CRM updates **Requirements:** - Experience with AI agent frameworks (LangChain, CrewAI, AutoGen, etc.) - Strong prompt engineering skills - Ability to integrate with our existing tools (CRM, calendar, email) - Past projects to show us – links or demos preferred **Budget:** Open to discussion based on scope **Timeline:** Looking to kick off within 1–2 weeks

We are hiring an AI Engineer for a remote opportunity with our Airlines project. The ideal candidate should have hands-on experience building GenAI solutions, including RAG pipelines, vector embeddings, prompt engineering, MCP server development, and integrating multiple LLM providers. Experience working with AWS Neptune (Graph DB), OpenSearch (Vector Store), Redis, REST APIs, and SSE-based streaming services is required. Exposure to LangChain, MCPSharp, or ModelContextProtocol.SDK is a plus. If interested, please share your updated resume along with your total years of experience, years of GenAI experience, RAG experience, MCP/Agentic AI experience, current location, work authorization, and availability to start.

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.

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

AI SYSTEMS ENGINEER Agentic AI, Multi-Agent Systems & Secure AI Workflows (U.S.) Remote • United States We're building production AI systems designed for enterprise environments. We're looking for exceptional AI systems engineers who enjoy solving difficult systems problems – not just writing code. Our work sits at the intersection of agentic AI, software architecture, enterprise systems, governance, security, and operational intelligence. We design AI systems that improve how organizations operate while meeting the standards required for production deployment. We value engineers who think in systems, challenge assumptions, and care deeply about building technology that is reliable, understandable, secure, and useful. If you're motivated by difficult engineering problems, thoughtful architecture, and building production AI systems for enterprise organizations, we'd like to hear from you. WHAT YOU'LL HELP BUILD Examples of the types of systems we design include: - Multi-agent AI systems - Enterprise AI assistants - Secure AI workflows - Enterprise workflow automation - AI-powered knowledge systems - Human-in-the-loop decision support - Document intelligence - Retrieval-Augmented Generation (RAG) - AI memory and retrieval systems - AI evaluation and testing frameworks - Secure enterprise AI platforms - AI governance capabilities - Operational intelligence platforms TECHNICAL EXPERIENCE WE VALUE We're interested in engineers with experience in some combination of: - Python - AI Agent Development - LangGraph - LangChain - Large Language Models - API Development - Vector Databases - Software Architecture - Enterprise Systems Integration - Information Security Experience with OpenAI, Anthropic, Model Context Protocol (MCP), cloud infrastructure, workflow orchestration, observability, distributed systems, or regulated technology environments is also valuable. We do not expect expertise in every technology. We care far more about engineering judgment, systems thinking, demonstrated execution, and continuous learning than checking every technology box. THE PROBLEMS WE ENJOY SOLVING The engineers who thrive here enjoy questions like: - How should multiple AI agents coordinate work? - How should humans remain in control of important decisions? - How should production AI systems scale safely? - How should memory be designed for enterprise AI? - How should AI systems balance operational performance with governance, security, and reliability? - How should AI systems create measurable business value? If those questions excite you, you'll probably enjoy working with us. WHAT MAKES SOMEONE SUCCESSFUL HERE We're looking for engineers who: - Think in systems rather than individual features. - Care deeply about production quality. - Enjoy solving ambiguous technical problems. - Communicate complex ideas clearly. - Balance speed with sound engineering judgment. - Build practical solutions rather than chasing hype. - Continuously learn, experiment, and improve. We're significantly more interested in systems you've built than technologies you've used. Please provide specific examples that demonstrate your role, engineering decisions, and measurable outcomes. We recognize that many engineers use AI as part of their workflow. You're welcome to do the same. However, your application should accurately reflect your own experience, judgment, and technical thinking. We respect the confidentiality of your current and former employers, clients, and partners. Please do not include proprietary or confidential information in your application. Describe your work at a level that demonstrates your engineering approach without disclosing protected information. PROFESSIONAL STANDARDS We value integrity, sound engineering judgment, and respect for intellectual property. Please do not include confidential, proprietary, export-controlled, or other non-public information belonging to your current or former employers, clients, or partners in your application or work samples. We're interested in your engineering approach, architectural thinking, and problem-solving methodology – not protected information belonging to others. If you share code, architecture diagrams, technical documentation, or project examples, please ensure you have the legal right to do so and identify any material open-source or third-party technologies where appropriate. By submitting application materials, you represent that you have the legal right to share them and that doing so does not violate any confidentiality, intellectual property, employment, consulting, or other contractual obligations. Any engagement, if offered, will be subject to a separate written agreement covering confidentiality, intellectual property ownership, compensation, and other applicable terms. Submission of an application or participation in the evaluation process does not create any employment, independent contractor, partnership, joint venture, agency, fiduciary, or other business relationship with 26ers AI, nor does it obligate either party to enter into any future engagement. 26ers AI reserves the right to evaluate applications, discontinue discussions, modify the hiring process, or decline to pursue any engagement at its discretion. Nothing in this posting should be construed as an offer of employment or an offer to contract.

We are building a next-generation workflow automation platform that combines deterministic business rules, artificial intelligence, document intelligence, and human review workflows into a single operating system. This is not a traditional CRM project. Our vision is to develop a doctrine-driven platform where business rules serve as the system authority, AI serves as an analytical and drafting layer, and human reviewers serve as the final compliance checkpoint. We are seeking an experienced engineer or engineering partner who can help architect and build the platform from the ground up. Project Objectives The platform will: • Ingest and analyze large volumes of structured and unstructured documents • Extract data from reports, PDFs, and supporting documentation • Apply rule-based workflow logic • Generate AI-assisted recommendations and draft outputs • Maintain complete audit trails and workflow transparency • Route work through human review checkpoints • Support future deployment of local AI infrastructure for privacy and performance Core Architecture The system will be built around four primary layers: 1. Rules Engine * Deterministic business logic * Workflow orchestration * State management * Trigger and escalation logic * Audit tracking 2. AI Layer * Document analysis * Classification * Pattern detection * Summarization * Draft generation * Structured outputs 3. Local Processing Layer * OCR * Document parsing * Data extraction * Vector search * Local inference capabilities * Privacy-first processing 4. Human Review Layer * Quality assurance * Workflow approvals * Compliance review * Exception handling Initial Development Priorities Phase 1 • User authentication • Client record management • Document upload system • OCR and document extraction • Workflow engine • Rule-based status management • Review dashboard Phase 2 • AI-powered document analysis • Automated classification • Recommendation engine • Draft generation workflows • Response parsing Phase 3 • Local AI infrastructure • Vector database integration • Knowledge retrieval system • Multi-agent workflow orchestration • Advanced automation Desired Technical Experience Required • React / Next.js • Node.js, Python, or similar backend framework • PostgreSQL or equivalent relational database • REST APIs • Cloud infrastructure (AWS, Azure, or GCP) • Workflow automation systems • Document processing pipelines Preferred • OpenAI APIs • Anthropic APIs • Retrieval-Augmented Generation (RAG) • LangGraph, LangChain, or similar frameworks • Vector databases • OCR technologies • AI agent architectures • NVIDIA AI ecosystem • Local model deployment What We Are Looking For We are not looking for someone who simply builds forms and dashboards. We are looking for a builder who understands how to combine: • Rules engines • Artificial intelligence • Workflow automation • Human review systems • Scalable software architecture The ideal candidate enjoys solving complex business process problems and translating expert decision-making into software systems. Engagement Structure Open to: • Fractional CTO • Lead Architect • Senior Full-Stack Engineer • AI Systems Engineer • Development Agency • Long-term strategic technology partner To Apply Please provide: • Relevant project examples • Experience building workflow automation platforms • Experience with AI-powered applications • Technology stack recommendations • Estimated availability • Preferred engagement structure

Title: Technical Delivery Lead / Orchestrator — AI & Automation Projects (Ongoing, Part-Time) Description: We're looking for a technically strong delivery lead to orchestrate AI and automation builds — not to do the hands-on coding (a dedicated dev team handles that), but to own the layer above it: scoping client needs, translating them into clear build plans, directing the dev team, and quality-checking what they ship. You'd be our technical point person on projects — comfortable on a call with a client or partner one minute, and reviewing the dev team's architecture the next. We need someone who can tell good work from bad, push back when something's off, and keep projects moving without being micromanaged. This is an ongoing, flexible, part-time role across a steady pipeline of work (marketing automation, agentic AI workflows, web/app builds). You'd start on one project to prove fit, then expand from there. Must-haves: - Strong technical background — you've built real things (read code, architect a solution, judge a dev team's work), with hands-on exposure to AI agents / automation (n8n, LangChain/LangGraph, or similar) - Client-facing polish — represent us professionally to clients and partners - Orchestration experience — you've scoped work and directed developers/teams, not just built it yourself - Based on the US West Coast — reliable overlap with both our team and an offshore dev team To apply, please include: To apply, just a few sentences on each: 1. One project where you scoped a client's need, directed a dev team, and delivered — what was yours vs. the team's 2. A line on your technical depth (something you've architected or built) and a line on client-facing work you've done 3. Your quick take: a client wants an "autonomous marketing system" live in 30 days — what's the first thing you'd want to know, and the most common reason these underdeliver? Keep it short — we're after sharp thinking, not a polished pitch. Individuals only — not agencies.

Description: I am looking for an experienced freelancer to help me build a centralized AI-integrated knowledge management system in Notion. This system will serve as the backbone for managing large-scale projects, organizing 1,000+ PDF documents, and leveraging AI tools for semantic search, automated categorization, and document summarization. It must be scalable, user-friendly, and designed to support long-term collaboration and growth. The ideal candidate will have expertise in Notion, AI integrations (e.g., Claude, OpenAI, LangChain), automation workflows (e.g., Zapier, Make, or APIs), and file management processes (including OCR). The system should be operational from day one, with all files uploaded, categorized, and fully searchable. Project Goals: 1. Fully Functional System in Notion: Create a centralized knowledge management hub in Notion to organize and manage all scanned files and documents. Upload and categorize 1,000+ PDF files into the system during setup. Build a clean, intuitive interface for managing projects, tasks, and documents. 2. AI Integration: Integrate AI tools (e.g., Claude, OpenAI, Notion AI) for the following: Semantic search: Search by meaning rather than keywords. Document summarization and tagging: Automatically generate summaries and metadata for files. Automated categorization: Categorize files by topics, projects, and metadata (e.g., project name, date, type). AI conversation logs: Enable collaborative decision-making and log AI-generated insights for shared review. 3. File Management and Automation: Automate workflows for importing, renaming, tagging, and categorizing files based on pre-defined rules. Ensure the system can handle OCR (Optical Character Recognition) to make PDFs fully searchable. Provide a blueprint for OCR settings, file-naming conventions, and file preparation best practices. 4. Collaborative Features: Enable multi-user access with role-based permissions for specific projects or categories. Set up dashboards and shared views for collaboration and task tracking. 5. Scalability and Independence: Design the system to handle thousands of files and multiple projects without performance issues. Provide training and documentation so I can independently manage and expand the system in the future. Deliverables: A. Scanning and File Preparation: Provide a step-by-step blueprint for scanning files, including OCR settings and file-naming conventions. Ensure all 1,000+ PDF files are uploaded, tagged, and categorized in Notion during setup. B. Notion Knowledge Base Setup: Build a clean and interconnected workspace in Notion with: Categories, tags, and metadata for file organization. Dashboards for managing projects, tasks, and documents. Automated workflows for file renaming and categorization. C. AI Integration: Integrate Claude, OpenAI, or Notion’s AI for: Semantic search and document summarization. Automated tagging and categorization based on file content. D. Collaboration Features: Set up shared access for multi-user collaboration with role-based permissions. Incorporate an AI conversation log feature to track collaborative decisions and insights. E. Testing and Final Documentation: Test the system with all files uploaded to confirm functionality. Provide a short video tutorial or detailed written guide explaining how to use, maintain, and expand the system. Requirements: The ideal candidate will have: Proven experience with Notion, including advanced setups and database design. Expertise in AI integrations, such as Claude, OpenAI, LangChain, or Notion’s native AI. Familiarity with OCR workflows, file automation, and document management best practices. Strong communication skills to provide clear documentation and training. A proactive approach to safeguarding data, including locking pages, setting permissions, and creating backups. Budget and Timeline: Budget: $900–$1,200 for the full setup and integration. Timeline: Completed within 2–3 weeks from project start. To Apply: Please include the following in your proposal: A brief overview of your experience with similar projects. Examples of previous work, including Notion setups, AI integrations, or file management workflows. Your proposed timeline and approach to completing this project. Any suggestions you have for improving the system.

About the Company: We are building the trust and compliance infrastructure for AI agents. Every AI agent gets a verified cryptographic identity, real-time behavioral enforcement, and signed compliance reports for EU AI Act, HIPAA, SOC2, and SR 11-7. The product is live and generating real compliance reports today. The Opportunity: The EU AI Act enforcement deadline is August 2, 2026. Every company deploying AI agents in healthcare, legal, finance, and insurance needs compliance infrastructure now. This is a time-sensitive market with identified buyers and a live product. The right person can earn significant commissions in a short window. The Role: We are looking for a hungry enterprise sales closer who lives and breathes the agentic AI world. You need to understand what AI agents are, how they are built, and why enterprises are terrified of deploying them without governance. You will be selling to CTOs, VP Engineering, and compliance officers at Series A and Series B AI companies. What You Will Do: - Outreach and follow up with warm and cold leads already identified - Run discovery calls and product demos - Close deals - Report weekly on pipeline progress What We Are Looking For: - Proven track record closing B2B SaaS or cybersecurity deals - Experience selling to CTOs, compliance officers, or VP Engineering - Hands-on experience building or working with AI agents — you must be able to speak the language fluently with technical buyers - Deep familiarity with the agentic AI ecosystem — LangChain, CrewAI, AutoGPT, OpenAI Assistants, MCP, or similar - Understanding of compliance requirements for AI systems — EU AI Act, HIPAA, SOC2, SR 11-7 is a strong plus - Self-starter who thrives on commission and owns their pipeline - US or European time zone preferred Compensation: - Commission only: 50% of first year contract value on every closed deal - No cap on earnings - Opportunity to grow into a full-time Head of Sales role as the company scales To Apply: Tell me about a specific enterprise deal you closed, who the buyer was, and how long the sales cycle took. Also tell me about your experience with AI agents — what have you built or worked with and how do you stay current in the agentic AI space.