We are seeking a highly experienced Advanced Artificial Intelligence instructor and curriculum consultant to design, customize, and deliver a private, instructor-led AI training program for a group of six participants. The program is expected to begin in October 2026 and may be delivered onsite in San Francisco, San Diego, or Los Angeles, California. The final location and schedule will be determined with the selected instructor and client. Program Overview This engagement is intended for experienced AI practitioners who can connect advanced technical concepts with practical enterprise implementation. The selected instructor will work with the client and NobleProg to determine the appropriate program duration, sequence the curriculum, customize the content, prepare hands-on labs, and deliver the training. The program should provide participants with practical knowledge of modern AI engineering, enterprise AI architecture, AI governance, large language models, production AI systems, and the infrastructure required to deploy and manage advanced AI solutions. Requested Curriculum Areas The proposed program should address the following subjects: AI governance, Responsible AI, and AI risk management Large language models and foundation models LLM training, fine-tuning, and distributed training LLMOps and production AI MLOps and AI platform engineering On-premises AI, private AI, and data sovereignty Agentic AI and multi-agent systems Retrieval-Augmented Generation Knowledge graphs and enterprise knowledge integration AI infrastructure and GPU clusters Distributed computing for AI workloads High-performance model inference AI security and model security Regulatory compliance and enterprise AI controls Enterprise AI architecture and deployment strategy The final curriculum may be adjusted based on participant backgrounds, available infrastructure, program duration, and the client’s technical priorities. Training Requirements The training should preferably be delivered as a private, instructor-led program and include: Practical exercises and demonstrations Instructor-guided hands-on labs Realistic enterprise AI use cases Participant training materials Lab instructions and supporting resources Recommendations for continued learning Certificates of completion Opportunities for participant questions and technical discussion Instructor Responsibilities The selected instructor will be responsible for: Participating in a client alignment and discovery meeting Assessing the participants’ technical backgrounds and learning objectives Recommending an appropriate course duration and training schedule Developing a proposed course outline Customizing the curriculum for the client Identifying participant prerequisites Defining all hardware, software, cloud, and GPU requirements Preparing practical exercises and hands-on labs Delivering the training virtually or onsite Providing training materials and supporting resources Recommending certificate or continuing education options Coordinating with NobleProg throughout the engagement Program Details Anticipated start: October 2026 Number of participants: Six Potential onsite locations: San Francisco, California San Diego, California Los Angeles, California Delivery options: Private onsite instructor-led training Private virtual instructor-led training A blended or hybrid schedule, when appropriate Applicants should indicate which locations and delivery formats they can support. Ideal Instructor Qualifications The ideal instructor will have substantial professional experience in several of the following areas: Enterprise artificial intelligence Machine learning engineering Large language model development and deployment Foundation model training or fine-tuning Distributed model training LLMOps and MLOps AI platform engineering Agentic AI and multi-agent architecture Retrieval-Augmented Generation Knowledge graphs GPU infrastructure and AI clusters High-performance model serving and inference Private or on-premises AI deployments Data sovereignty and regulated data environments AI governance and Responsible AI AI security, compliance, and risk management Enterprise AI architecture Previous experience delivering advanced instructor-led training to corporate, government, engineering, or technical audiences is strongly preferred. Relevant certifications, publications, conference presentations, open-source contributions, enterprise projects, or academic credentials should be included in the application. Proposal Requirements Please provide the following information with your application: A summary of your relevant AI experience Your instructor-led training experience Your experience with enterprise or government clients Your recommended course duration Your proposed training schedule A preliminary course outline Recommended technical prerequisites for participants Required participant software and development environments Required cloud platforms, GPU resources, or local infrastructure Your ability to support virtual delivery The onsite locations you can support Your availability during October 2026 Relevant certifications and professional credentials Examples of similar training programs you have delivered Certificate or continuing education options you can support Any applicable corporate, government, or group-training considerations Confirmation that you accept the stated daily rate Please clearly identify which curriculum topics you can teach directly and whether any portions of the program would require an additional specialist. Compensation Training rate: $1,200 per day of training delivery The final project compensation will be determined by the approved number of training days. The agreed compensation is expected to cover: One client alignment and discovery meeting Curriculum planning Training material preparation Reasonable curriculum customization Hands-on lab preparation Instructor-led training delivery Reasonable local travel expenses, including gas, Uber, and parking, will be reimbursed when necessary and approved in advance. Any airfare, lodging, extended-distance transportation, specialized cloud environments, GPU resources, software licenses, or other significant expenses must be disclosed and approved before the engagement begins. Payment Terms Payment milestones and invoicing terms will be finalized before the engagement begins. Applicants should disclose any required deposits, cancellation terms, or other payment conditions in their proposals. Important Links Additional program and curriculum details: https://docs.google.com/document/d/1EZ4KRYCaZZYtg3JX4eSu82H3pmjCRxEguHCbbTD7yJ0/edit?usp=sharing NobleProg instructor process and SOP: https://share.synthesia.io/a0788c6e-56d5-4da8-92c6-0d5c03ad6d52 Please review both links before submitting your application. How to Apply Begin your application with the phrase “Advanced Enterprise AI Instructor” to confirm that you have reviewed the complete posting. Please submit a focused proposal that explains how you would structure this program for six participants, including the number of days you recommend, the balance between lectures and labs, and the infrastructure required to complete the hands-on exercises successfully.

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.

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.

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.

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.

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 cross-organizational AI agent trust and identity layer for regulated financial transactions. Our stack includes LangGraph (orchestration), Supabase (database + RLS), Clerk (identity), and Cloudflare Workers (API gateway). We need a Principal-level architect to conduct a one-time, 3-hour architecture validation session to stress-test our design BEFORE we write production code. THIS IS NOT A DEVELOPMENT JOB. This is an advisory/review engagement only. WHAT YOU REVIEW: - Agent identity model (registration, verification, scoping, revocation, cryptographic attestation) - Trust token protocol (issuance, verification, revocation, replay attack vectors, network partition behavior) - Compliance checkpoint architecture (GLBA/RESPA/E-SIGN rule placement, audit trail immutability, human approval gates) - Five-layer system architecture (Cloudflare → LangGraph → Supabase → Clerk → external integrations) WHAT WE PROVIDE 48 HOURS BEFORE THE SESSION: - Full architecture diagram and documentation - Pre-flagged findings from our AI agents (Compliance, Security, Architecture agents have already reviewed the docs — you validate their findings and catch what they missed) DELIVERABLE: - Written architecture review (2-4 pages) with: - Approved decisions (green) - Required changes (red — must fix before building) - Recommended changes (yellow) - Open risks - Explicit go/no-go on proceeding to build phase REQUIREMENTS: - Must have designed and shipped a production identity, auth, or trust system (not just configured one) - Experience with token-based auth (OAuth, JWT, mTLS) - Understanding of zero-trust architecture and agent identity - Ability to think adversarially (attack vectors, bypass scenarios, failure modes) - NDA required before any technical documentation is shared BUDGET: - Flat fee for the full engagement (pre-read + 2-hour session + written deliverable) - Please quote your rate in your proposal IF THIS SESSION GOES WELL: - We have 4 additional review sessions over the next 6 months (identity layer code review, trust token implementation, orchestration + API review, pre-pilot pentest readiness) TO APPLY: - Confirm you have shipped a production identity or trust system (name the company/project if possible) - State your flat fee for this engagement - State your availability for a 15-minute intro call this week - Include any relevant architecture review samples or past work Do NOT apply if you are an integrator, administrator, or generalist developer. We need someone who has ARCHITECTED identity systems from scratch.

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.

Type: Hourly, ongoing (part-time to full-time, room to grow) Stack you'll work in: Notion, Slack, HubSpot, Google Workspace/Gmail, Claude + other LLM APIs, Zapier/Make/n8n About us We're a fast-moving sports and fan-engagement startup. We're small, we ship quickly, and we want AI woven into how the whole company operates, not as a side experiment, but as the default way we work. You'd be the person who makes that real. What you'll do Map our current workflows across sales, marketing, ops, and content, then find the highest-leverage places to automate. Build automations and agent workflows that connect our tools (Notion, Slack, HubSpot, Gmail/Google Workspace) using platforms like Zapier, Make, or n8n plus LLM APIs. Design and ship AI agents for real jobs: lead routing and CRM enrichment, content drafting, customer/fan response triage, internal knowledge search, reporting digests. Stand up the connective tissue (prompts, integrations, guardrails, and monitoring) so automations are reliable, not brittle demos. Train and enable our team: build SOPs, run working sessions, and create lightweight docs so non-technical people actually adopt what you build. Help set our AI strategy and roadmap as we scale. You're a strong fit if you Have shipped real automations and AI agent workflows in production (not just prototypes). Are fluent with Zapier / Make / n8n and at least one major LLM API (Anthropic/Claude, OpenAI). Know your way around HubSpot, Notion, Slack, and Google Workspace integrations and APIs. Can write clean prompts and think in systems: edge cases, error handling, human-in-the-loop checkpoints. Can explain technical work to non-technical people and get them to adopt it. Communicate proactively and move fast without breaking trust on things that touch customers or revenue. Nice to have Experience taking a small company "AI-native" end to end. Background in sports and/or blockchain. Comfort with light scripting (Python/JS) when no-code hits its limits. How to apply In your proposal, please: Describe one AI agent or automation you built, the tools involved, and the measurable result. Tell us how you'd approach training a non-technical team to actually use what you build. This part matters as much as the build. Share your hourly rate and weekly availability. Proposals that skip these will be passed over. We're looking to start with a small paid task and grow the engagement from there.

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.