Catalyst·Wayfare is an AI transformation firm that ships working systems — production AI for mid-market enterprises in regulated and technical domains. We don't stop at PowerPoint strategy; we build and deploy in partnership with our clients and their engineering teams. The team's backgrounds span MIT, McKinsey, the White House, and some of the most respected names in tech.
The role. You'll embed inside the engineering organization of a leading firm in a critical-infrastructure sector, where the binding constraint on revenue is technical throughput the labor market can't supply. You own the agent system that lifts it. This is a forward-deployed seat — GitHub history, not Salesforce dashboards. You write the code; we manage the room. The work is technically interesting (multi-agent orchestration over real domain simulators, not chatbot demos) and commercially serious (review gates tied directly to billable throughput). We're looking for someone who codes like an IC, communicates like a PM, and navigates clients like a founder. You own architecture, the orchestration engine, and the agent design patterns we replicate at the next client.
How we ship. Claude and OpenAI APIs in production; open-source models (Llama, Mistral) when the data or the math points there. Cursor and Claude Code in our IDEs, daily. Vercel, Neon, and Sentry on our deploy surfaces. Evals are first-class artifacts, not an afterthought — and you won't be the engineer fighting a CISO to install Cursor.
What you'll do
- Lead architecture and build of a multi-agent orchestration platform spanning roughly seven capability agents: data ingestion, requirements retrieval, model construction, simulation orchestration, QA, report generation.
- Define interface contracts with the client's software team for integration into the domain-specific simulation tools their business depends on.
- Design and build the orchestration engine: state management, error recovery, audit trails, monitoring dashboards.
- Build on existing data foundations — a production RAG system with established retrieval infrastructure and live interaction telemetry.
- Run a tiger-team pilot loop with the client's senior engineers: instrument, measure time savings, capture failure modes, refine.
- Embed on-site periodically (heavier the first quarter, lighter after), traveling to a single U.S. major metro roughly monthly.
- Mentor a junior builder and help shape technical hiring as we grow.
Must-haves
- Six-plus years building production software, with two-plus years shipping LLM-based or agentic systems in production (not POCs that died).
- AI-pilled and full-stack — you reach for agents instinctively and have opinions about which ones — but you got fluent with code first. Cursor multiplies you; it didn't teach you.
- Strong Python, comfortable with at least one agent framework (LangGraph, Letta, or custom orchestration), and the judgment to know when to roll your own.
- Hands-on RAG: vector databases, embedding models, document-processing pipelines, retrieval evals.
- Strong intuitions for LLM evals and agent reliability — you've debugged a system from 70% to 95%.
- Comfortable as the technical voice in client-facing rooms with non-engineers, executives, and domain experts.
- Clear written communication and willingness to overlap with (not mirror) U.S. Eastern hours.
Nice-to-haves
- Prior forward-deployed or solutions-engineering experience at an AI lab, applied firm, or similar.
- Integrating LLMs with deterministic engineering tools, simulators, or specialized APIs.
- Cloud infrastructure (AWS, Azure, GCP) for deploying production AI.
- Domain exposure to regulated or technical verticals (financial services, healthcare, legal, industrial).
We're flexible on years of experience if the work history shows the right shape — a strong mid-level engineer with a sharp track record of shipping agentic systems will be considered.
Logistics
- Type: Full-time or contract (technical lead seat)
- Term: 8 months, extension likely
- Location: Remote-first, U.S. Eastern overlap; ~monthly U.S. domestic travel to one major metro
- Reports to: the Catalyst·Wayfare founder
How to apply Email [email protected] with "Lead AI Engineer - Agentic Systems" in the subject line, and include three things: (1) a short cover letter — who you are, what you've shipped, why this seat; (2) a short note, three to five paragraphs, on a multi-agent or production LLM system you built — what worked, what broke, what you'd do differently; (3) GitHub, code samples, or CV — optional, only if they sharpen the above.
