Senior Forward Deployed Engineer - AI Architect

What you'll own

This role is measured on outcomes delivered, not tickets closed or hours billed.

• Own a client outcome end to end. The business result the client is paying for, from ambiguous first conversation to production system.


• Command a pod. Associate FDEs and AI agents are your team from day one. You set technical direction, review their work, and are accountable for what the pod ships.


• Architect and ship into production. Inside the client's actual security model, data residency rules, and legacy stack.


• Operate as the engagement's de facto CTO. Translate an ambiguous client problem into scope, and scope into shipped software, without waiting for someone else to define the spec.


• Leave the client's team stronger. Transfer capability and documentation. A good engagement reduces the client's dependency on us, not increases it.


• Say the hard thing. To the client, when the scope is wrong or the timeline is fiction.

Who thrives in this role

• 6–10 years shipping production software, with meaningful time in customer-facing, embedded, or consulting-adjacent delivery.


• Has already put an agentic system into production inside a regulated or otherwise constrained environment — not a demo, not a hackathon.


• Has led a small team, formally or informally, and is comfortable being one of a handful of senior people that associate engineers look to for direction.


• Uses agentic coding tools as a default working method, not a novelty.


• Has sat across the table from a client's engineering, security, and compliance teams simultaneously, and gotten to yes.


• Wants to be evaluated on outcomes delivered, not hours logged.

What we evaluate, and where

What \'good\' looks like

Where it's tested

Has shipped and operated systems at scale; reasons about failure modes, not just the happy path

Technical work sample

Applied AI / agentic systems

Has built with LLMs and agents beyond prompting — RAG, tool use, evals, orchestration

Technical work sample + technical interview

Uses agentic tools as a default method of building, evaluated live

Live pairing session, your own tools

Regulated-industry delivery

Has navigated SSO, data residency, model risk, or equivalent real-world constraints

Case interview

Client-facing judgment

Separates signal from noise in an ambiguous, high-stakes client ask

Case interview

Leadership and teaching ability

Explains the same technical decision differently to a junior engineer and to a client CTO

Pod-fit conversation with current FDEs

AI fluency is a baseline requirement here, tested directly.

What this role is not

• Not staff augmentation. You own an outcome, not a backlog assigned by a client PM.


• Not advisory. You ship production code. If the engagement doesn't produce shipped software, it doesn't count.


• Not tied to one vendor. You'll work across Anthropic, OpenAI, Google, SpaceXAI, and NVIDIA stacks depending on what the client's problem requires — not a single-platform mandate.


• Not remote-first. This role lives at the client site during active engagements.