AI Trainer

What We Look For

Role summary

You will design and deliver hands-on AI training for enterprise clients. Sessions are mostly virtual and run in 3–4 hour blocks across global time zones. Audiences range from executives to software engineers. Builder cohorts work in the labs themselves: skills, agents, MCP servers, coding agents, code review. Leader and enabler cohorts work on everyday workflows. You co-facilitate with other Metis trainers and tailor the content to each client’s industry, tools and security requirements. You own keeping content current. Models, tools and pricing change quarterly, so you update materials before each cohort.

Must-have

Technical depth

• You have shipped LLM or agentic systems to production, not just prototyped them. You can show examples.
• You are fluent in how agentic coding harnesses work: context files (CLAUDE.md / AGENTS.md), skills, subagents, hooks, MCP and plugins. You have built a custom MCP server and an agent end to end.
• You know the main ways to extend a model (prompting, RAG, fine-tuning, self-hosting) and can explain when to use each.
• You understand agent security: prompt injection, least-privilege tools, human-in-the-loop and guardrails outside the model.
• You can explain Tokenomics and cost control to both engineers and finance audiences.

Ecosystem breadth

• Hands-on with Anthropic (Claude, Claude Code, Cowork), OpenAI (ChatGPT, Codex, SDKs), Microsoft (M365 Copilot, Copilot Studio, Copilot Cowork, GitHub Copilot) and open-weight models.
• Working familiarity with Google (Gemini, Vertex), AWS (Bedrock), Cursor and the major agent frameworks (LangGraph, CrewAI, MS Agent Framework).

Teaching and facilitation

• You have taught live, technical, hands-on sessions to groups, in person or virtual.
• You pace a 4-hour virtual session well: polls, breakouts, chat, energy management and a clean break structure.
• You troubleshoot setup problems in locked-down enterprise environments (Windows, WSL2, proxies, restricted installs, SSO and licensing) without losing the room.
• You can explain complex concepts plainly to different audiences, and you stay calm when a live demo misbehaves. Models are non-deterministic, so demos will sometimes fail.

People skills (observable)

• You read a remote room and adjust. You can tell who is lost, who is bored and who is already ahead.
• You handle skepticism and job-displacement anxiety directly, without dismissing it.
• You are comfortable saying “I don’t know, let’s test it.”

Experience

• 10+ years in software development, data/ML engineering, architecture or technical product work, with recent, practical experience building with LLMs.

Strong plus

• Consulting or client-facing delivery experience, including working under a partner brand and co-facilitating.
• Governance and compliance fluency: responsible AI, data classification, and regional requirements such as the EU AI Act and data residency.
• Evals and observability experience: building test sets, guardrails and monitoring for LLM applications.
• Instructional design: building labs, measuring learning with pre/post assessments, and reinforcing it afterward (office hours, 30/60/90-day follow-through).
• Change management or AI adoption experience, including connecting training to business outcomes and ROI.
• Domain experience in a regulated or industrial sector (manufacturing, IT/OT, healthcare, financial services).
• Experience authoring skills, plugins or reusable templates that a client team can maintain.

Nice to have

• Experience teaching across cultures and non-native English audiences (for example India, EMEA and North America in the same program).
• Public thought leadership: writing, talks or open-source work.
• Self-hosted inference and fine-tuning experience (vLLM, Ollama, LoRA/QLoRA).

What Metis Strategy Has to Offer

Successful candidates will be motivated by the desire to make a difference by helping our clients achieve and maintain strategic and operational excellence while continuously improving their own skill set and embracing emerging intellectual challenges.

This position is also eligible for bonus compensation. Additional benefits include but are not limited to:

• comprehensive medical insurance, dental insurance, and vision insurance;
• parental leave, and family benefits; 
• retirement contributions;
• stipend for continued learning;
• paid time off, and more. 

Compensation and benefits are competitive and will be commensurate with each candidate’s qualifications and relevant work experience. 

If you are driven by the desire to help some of the world’s most renowned companies solve complex business problems and excited by the intersection of business strategy and technological innovation, you will enjoy being a part of our team.