Hi I am looking to create an AI agent that is friendly with Copilot but could work with other common AI platforms. Details: An AI RFP agent to streamline the entire procurement process by drafting RFPs, recommending deliverables, checking for missing requirements, and ensuring USDA/AMS compliance. It could automatically compare vendor proposals, score them against predefined criteria, identify risks and gaps, recommend vendors based on past performance, and generate executive summaries and recommendation memos. Once a vendor is selected, it could also create statements of work, project timelines, and contract milestones while capturing lessons learned to continuously improve future RFPs. The result is a faster, more consistent, and more strategic procurement process that allows the team to spend less time on administration and more time selecting the best partners.

We are seeking an experienced developer to build an AI agent. A description of the agent is provided in the posting. The ideal candidate will have a strong background in AI development and be able to work on various platforms. The agent will be need to extract information from multiple sources (documents and spreadsheets) and tools (Salesforce, Apollo, other) to create a final output.

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.

About us: Luxe Intelligence is a Baltimore based AI consulting firm. We design and deliver custom AI agent systems for business clients, including regulated industries, with a growing security and government-adjacent practice. We design the system and own the client relationship. You build to spec. The kind of work: Real examples of project types on our roadmap: - Data matching and compliance checking agents that cross-reference large lists (10,000+ rows) with no shared ID, using fuzzy name matching, confidence scoring, and human review flags - Research agents that pull from defined sources and produce structured memos with citations, and say "unverified" instead of guessing - Workflow automations across webhooks, spreadsheets, CRMs, Slack, and email - Read and write-back integrations with systems of record like Salesforce - Deployments inside client cloud environments with audit logging and security review support Must haves: - Strong Python, including pandas and API work - Hands-on experience with LLM APIs (Anthropic, OpenAI): prompt design, structured outputs, cost control - Fuzzy matching or entity resolution experience on real data - Cloud deployment on AWS, Azure, or GCP - Security-minded engineering as a habit, not an afterthought: secrets management, least-privilege access, encryption in transit and at rest, audit trails, human-in-the-loop review steps - Clear written English and documented handoffs Nice to have: - A real cybersecurity background: security engineering, compliance frameworks (SOC 2, NIST, FedRAMP awareness), or secure deployment in regulated environments - US citizenship with eligibility for a government security clearance, or an active clearance, is a plus and worth mentioning - Make.com or similar automation platforms - Salesforce API - Experience answering client security questionnaires How we work: Fixed-price milestones scoped from agreed hour estimates, paid on delivery and approval. NDA signed before any project details are shared. No client contact; all communication runs through Luxe. Some overlap with US Eastern hours. Every engagement starts with one small paid test milestone. Strong performance can grow into a larger ongoing role. To apply, answer these four things, and start your reply with the word CHARCOAL so we know you read this far: 1. Describe a fuzzy matching or entity resolution project you built. How big was the data, and how did you score confidence? 2. Describe an LLM-powered system you deployed into someone else's environment. What broke, and how did you fix it? 3. Estimate this: two lists, about 10,000 rows and 2,000 rows, no shared ID. Need matches, confidence scores, and a monthly flagged-items report. Roughly how many hours, broken down however makes sense to you? 4. Your hourly rate, your weekly available hours, and any security or clearance background.

I need a freelancer to build an AI agent for one simple task. The task involves scraping data from a webpage on a daily basis and then posting that data to an excel document on a daily basis. The task would then run automatically and keep copies of the screen shots so that the data can be verified.

AI Architect & Autonomous Agent Engineer (Full-Time, US-Based) Own a Live Production Agent Fleet WHAT THIS IS I run a small, profitable company with an unusual amount of automation behind it. A fleet of autonomous AI agents runs our internal data operation unattended for roughly 12 hours a day, every day. It is real production infrastructure that the business depends on. This is not a "build me a chatbot" job and it is not greenfield. The system exists, it runs daily, and mistakes cost real money. Multiple independent pipelines run in parallel, each doing multi-stage automated research, each calling paid third-party APIs at several points, each with its own quality gates and delivery step. Tens of thousands of records have moved through it. I have been operating and extending this system myself. I need someone to own it so I can stop being the bottleneck. This is an architect role and a builder role at the same time. You will design the system AND write the code AND debug it at 6pm when an agent has done something confident and wrong. There is no team under you to hand it off to. If that split appeals to you, keep reading. I will describe the domain and the specifics on a call, under NDA. What I can tell you publicly is the engineering problem, which is below and is genuinely the interesting part. WHAT YOU WOULD OWN 1. ARCHITECTURE AND AGENT DESIGN - Own the overall design: how the pipelines fit together, where state lives, what runs where, and what happens when any piece fails - Build and maintain autonomous agents that run for hours without a human watching, using Claude Code and Codex - Design the guardrails: quality gates, fail-closed checks, regression tests,and audit trails so an agent cannot silently ship bad work - Debug agents that did the wrong thing confidently, which is the hard part 2. MULTI-DEVICE FLEET ORCHESTRATION - Scale from one machine to many machines running the same pipelines at once - Solve the coordination problems that come with that: shared claim and lock systems so two machines never do the same paid work twice, distributed state, race conditions, safe failure modes - Build the setup and sync tooling so a new machine can be onboarded quickly and every machine runs identical, current logic 3. INTEGRATIONS AND DATA PLUMBING - Cloud spreadsheets and file storage used as coordination and reporting layers across machines - Several third-party vendor APIs, some of them metered and billed per call - Reporting that a non-engineer can actually read and trust 4. QUALITY AND COST CONTROL - Every paid API call should be justified and never duplicated - Build measurement into the system so we know our unit cost and can improve it deliberately, not by guessing WHO THIS IS FOR You will do well here if: - You have shipped agentic systems that run unattended, not just prompts that work in a demo - You think like a systems engineer: idempotency, locking, retries, race conditions, failing closed, and knowing the difference between "it returned 200" and "it actually worked" - You are comfortable in Python, APIs, and the command line - You test your own work adversarially and assume your first answer is wrong - You can explain a technical tradeoff to me in plain language without making me feel stupid or hiding the risk - You are comfortable working on something you cannot put in a public portfolio You will not do well here if you need tickets written for you, if you have only worked on greenfield projects, if you want to architect without implementing, or if you are more excited about model choice than about whether the pipeline is correct at 2am with nobody watching. LOGISTICS - Full-time, long-term. This is an ownership role, not a one-off project. - US-based required. Significant overlap with US Eastern hours. - NDA before we get into specifics. HOW TO APPLY Skip the generic cover letter. I will read all of these and ignore anything that looks templated. Please answer these three questions: 1. Describe an autonomous system you built that ran without supervision. What broke, how did you find out, and what did you change so it could not happen again? 2. Two machines are running the same pipeline against a shared queue of work items. Each item costs money to process. How do you make sure no item is ever paid for twice, and what happens when one machine dies mid-task? 3. What is a mistake an AI agent made in something you built that you did not catch until it had already caused damage? Short and specific beats long and polished. If your answer to #2 is one paragraph and correct, you are ahead of most applicants.

I’m looking for a Los Angeles based, strategic, technically skilled AI builder, preferably who is also great at teaching what they are building. In this role, you will need to be able to think architecturally, document processes, and co-create AI systems that are ethical, elegant, and deeply aligned with human-centered leadership for both our company and for clients. This role is best for someone who wants a long term client for creating meaningful, high-quality AI systems that serve real businesses. The ideal candidate is: Based in Los Angeles for occasional in-person work sessions Fluent in English (clear written and spoken communication is essential) Comfortable being on camera (Zoom calls + recording walkthroughs and build processes) Highly organized and systems-oriented Energized by emerging AI tools and agent frameworks Values-driven and excited by conscious, ethical business Experienced in building AI agents and automations Has strong understanding of APIs and integrations To apply for this role, send me: A short note about your experience building agentic AI systems Tools you use (be specific) A Loom or video walkthrough of a build you’ve done Where you are located, and what hours you regularly work with clients If you’re excited about building the future of intelligent systems and doing it inside a values-driven business, I’d love to hear from you.

Create ai agents for small businesses. Ai voice receptionist to schedule appointments and integrate with business owner schedule. Ai agent to send a text after a call with the objective of booking an appointment. Ai agent to send a text to follow up on estimates. Ai agent to scan through old leads and send a text to get more sales.

We are looking for an experienced AI Architect / Senior LLM Engineer to design and build an enterprise-grade AI platform for the healthcare industry. You will lead the architecture and implementation of intelligent AI solutions that improve clinical operations, automate administrative workflows, and enable healthcare professionals to access trusted medical knowledge through advanced AI technologies. The ideal candidate has hands-on experience building production-ready Agentic AI systems, Multi-Agent architectures, RAG pipelines, and LLMOps using modern AI frameworks and cloud platforms. Responsibilities Design and develop scalable Agentic AI solutions for healthcare applications. Build Multi-Agent Systems using LangGraph, CrewAI, or AutoGen. Develop enterprise Retrieval-Augmented Generation (RAG) pipelines for medical knowledge retrieval. Create AI agents for clinical knowledge assistance, document intelligence, workflow automation, and care coordination. Build and integrate MCP servers and custom AI tools with internal healthcare systems. Optimize prompt engineering, retrieval strategies, and response quality for high accuracy. Implement AI guardrails, evaluation pipelines, monitoring, and observability for production deployments. Deploy secure, scalable AI infrastructure on AWS using Infrastructure as Code and CI/CD best practices. Collaborate with engineering, product, and healthcare stakeholders to deliver reliable AI solutions. Required Skills 5+ years of experience in AI/ML or Generative AI development. Strong expertise in Python and backend API development. Experience with LangGraph, CrewAI, AutoGen, or similar multi-agent frameworks. Hands-on experience with AWS Bedrock, Azure OpenAI, or Vertex AI. Strong understanding of RAG architectures, vector databases, embeddings, and semantic search. Experience with Pinecone, Weaviate, pgvector, or similar vector databases. Knowledge of LLMOps, evaluation frameworks, prompt engineering, and AI observability tools. Experience with Docker, Terraform, CI/CD, and cloud-native deployments. Familiarity with healthcare compliance, security, and responsible AI practices is highly preferred. Preferred Technologies LangGraph CrewAI AutoGen AWS Bedrock Claude GPT-4o Gemini Pinecone pgvector LangSmith Arize Phoenix FastAPI Docker Terraform GitHub Actions MLflow Nice to Have Experience developing AI-powered healthcare platforms. Knowledge of healthcare workflows, clinical documentation, or medical knowledge systems. Experience integrating AI solutions with enterprise applications through APIs and MCP. Familiarity with AI governance, model evaluation, and production monitoring. If you are passionate about building enterprise-scale AI solutions that transform healthcare through Agentic AI and Generative AI, we'd love to hear from you.

Looking for an experienced AI developer to help build an AI agent using Claude. Requirements: Experience building AI agents and autonomous workflows Strong experience with Claude and Anthropic models Ability to integrate external data sources and APIs Experience deploying production-ready AI solutions Please include: Examples of similar AI agent projects you've built Your experience with Claude Your recommended tech stack Estimated timeline and cost Looking to start immediately.