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.

### Job Description: AI Chatbot Developer We are excited to announce an opening for an experienced and innovative developer to join our dynamic team in the pursuit of creating an advanced AI Chatbot. This chatbot will be designed to perform essential business functions, including but not limited to lead generation, quoting, and providing exceptional customer support. Our ideal candidate will possess a robust background in AI technologies, particularly in the realm of chatbot development, and will be equipped with outstanding problem-solving skills that enable them to tackle complex challenges with creativity and efficiency. As a key member of our development team, you will collaborate closely with various departments to gain a comprehensive understanding of our specific operational needs and requirements. Your ability to translate these needs into a functional and user-friendly chatbot solution will be critical to enhancing our overall operational efficiency. We are looking for someone who is not just technically proficient but also possesses a keen sense of business acumen to ensure that the chatbot aligns with our strategic goals. In this role, you will be responsible for various aspects of the chatbot development lifecycle, including but not limited to: - Designing and developing the conversation flow and user interface of the chatbot, ensuring it is intuitive and engaging for users. - Implementing natural language processing (NLP) capabilities to enable the chatbot to understand and respond to user inquiries accurately. - Integrating the chatbot with existing systems and databases to facilitate seamless access to information necessary for lead generation, quoting, and customer support functions. - Conducting rigorous testing and quality assurance to ensure the chatbot performs reliably and meets user expectations. - Analyzing user interactions and feedback to continuously improve the chatbot's performance and expand its capabilities over time. - Staying current with the latest advancements in AI technologies and chatbot development to incorporate best practices and innovative solutions. You will also play a crucial role in training team members on how to utilize the chatbot effectively and will be expected to provide ongoing support and maintenance to ensure the chatbot remains up-to-date and functional. If you have a passion for artificial intelligence, a deep understanding of customer engagement strategies, and a desire to make a significant impact within our organization, we would love to hear from you! Join us in revolutionizing the way we interact with our customers and streamline our business processes through cutting-edge technology. This is a fantastic opportunity for someone looking to advance their career in a fast-paced, forward-thinking environment. Apply today and be part of our exciting journey towards enhancing our customer experience through AI!

I’m seeking an expert for a project-based engagement to design and build an agentic AI-powered investor relations (IR) capability that automates key aspects of the IR function while maintaining appropriate regulatory and disclosure compliance. The objective is to create a system that can develop and consistently reinforce a strategic corporate narrative, identify relevant industry themes and opportunities, and generate high-quality investor-facing content that positions the client company as a recognized subject-matter expert and thought leader in embodied intelligence. The ideal candidate will have experience with agentic AI systems, workflow automation, LLM-powered content generation, financial communications, and/or investor relations, with a strong understanding of the compliance considerations associated with communications by public companies.

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.

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.

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.

I am seeking a highly qualified independent technical expert to review my professional work and, if appropriate based on your independent assessment, prepare an expert opinion letter for an employment-based U.S. immigration matter (EB-1A). The ideal candidate should have: Sr Faculty in reputed university, Ph.D. or equivalent senior industry expertise Oil and Gas, Computer Science, Artificial Intelligence, Cloud Computing, Data Engineering, or a related discipline. 15+ years of experience in the Oil & Gas or Energy industry. Recognized expertise in AI, machine learning, cloud architecture, digital transformation, industrial IoT, operational data platforms (e.g., AVEVA PI, OSDU), or enterprise data management. Strong technical writing skills and the ability to clearly explain complex engineering concepts. The engagement would involve: Reviewing my published articles, technical documentation, project summaries, and supporting materials. Independently evaluating the originality, technical significance, and industry impact of my work. Preparing an objective expert opinion letter describing your assessment of my contributions, their technical significance, and their relevance to the broader energy industry, if supported by your independent review. The letter should reflect your own professional judgment and be based solely on your independent evaluation of the materials provided. Please include with your proposal: A résumé or CV. A brief summary of your experience in AI, cloud technologies, digital transformation, or energy systems. Any prior experience serving as an expert witness, peer reviewer, technical evaluator, or preparing independent expert opinions (if applicable). Confidentiality will be required before project materials are shared.

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.

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.

MNT AI USA Suite 210, 1555 Naperville Wheaton Road, Naperville, IL 60563 AI Associate Instructor Location: Naperville, IL (in-person, Suite 210) | Job Type: Full-Time MNT AI USA is looking for an AI Associate Instructor to join our Naperville team and help small businesses put AI to work. In this role, you'll teach practical, hands-on training on today's leading AI tools and guide business owners through real implementation, not just theory. If you love using AI tools daily, explaining them clearly, and watching a room have that "aha" moment, we want to talk to you. What You'll Do • Deliver in-person training sessions and workshops for small business owners and their teams on how to use AI tools effectively in day-to-day operations. • Teach both the theory (how these tools work and when to use them) and the practical, hands-on application (how to actually implement them for a real business need). • Build customized curriculum, demos, and exercises tailored to different industries and business use cases. • Work hands-on with tools including Claude, ChatGPT, Perplexity, Design Arena, Replit, Notebook LLM, Base44, and similar AI platforms. • Help clients identify practical, value-adding AI use cases for their business, from content and research to automation and workflow tools. • Stay current on new AI tools, features, and best practices, and continuously update training materials accordingly. • Answer client questions, troubleshoot tool issues, and provide ongoing support as needed. • Collaborate with the MNT AI USA team, including the Entry-Level AI Instructor, to refine training programs based on client feedback and outcomes. What We're Looking For • Prior hands-on experience with AI tools is required. You should already be comfortable using platforms like Claude, ChatGPT, Perplexity, Replit, and similar tools in real projects. • Prior knowledge of AI concepts and applications is required; this is not an entry-level introduction to AI. • Strong communication and presentation skills. You can explain technical concepts in plain language to non-technical audiences. • A teaching, training, or coaching background is a plus, but a genuine passion for helping others learn matters just as much. • Comfortable working in person at our Naperville office and leading live sessions. • Self-starter who can build and adapt training content independently. • Business or consulting mindset, able to translate AI capabilities into practical value for small businesses. Application Requirement As part of the interview process, candidates must be prepared to present a business case they personally built using AI tools. During the technical round, you'll be asked to walk us through what you created, which tools you used, and the value it delivered. Why Join MNT AI USA • Be part of a growing company at the forefront of helping small businesses adopt AI. • Work directly with business owners and see the real-world impact of your training. • Collaborative, in-person team environment in Naperville, IL. How to Apply Submit your resume along with a brief note on your experience with AI tools. Be ready to demonstrate your AI-built business case during the technical interview.