[Hiring] Forward Deployed AI Engineer @FullStack

Role Description

Forward Deployed Engineers sit inside the client’s problem, not next to it. You embed with an enterprise team, find the work that actually warrants AI, architect the system, build it, and stay long enough to make it survive contact with production.

This is a three-way role: consultant, operator, engineer. You should be as comfortable pressure-testing a business case with a COO or VP of Engineering as you are diagnosing why retrieval quality collapsed after a data refresh. The people who succeed here can hold a discovery conversation on Monday and ship what they scoped on Thursday.

On this track, your edge is data, retrieval, and model behavior: you make agents trustworthy by getting the data, context, and evaluation right.

We work with regulated industries and Fortune 500 clients who have AI mandates, real constraints, and low tolerance for demos that don’t hold up.

How We Approach The Work

• FDEs are trusted to shape the solution, not only deliver it.
• Every engagement calls for architect-level judgment:
• Reframes the request. Treats “we need an agent for X” as a hypothesis, not a spec.
• Decomposes the problem. Outcome → process → decisions → data → systems → actors → constraints — before choosing technology.
• Chooses the intervention. Remove, simplify, traditional software, automation, LLM, RAG, agent, or multi-agent — and defends why.
• Owns the architecture decision. Documents trade-offs (ADRs), sets success metrics, pushes back on scope that won’t deliver value.

Consultative Discovery

• Clients rarely arrive with a fully formed problem, and the FDE’s first contribution is helping them see it clearly.
• You lead discovery with genuine curiosity, moving the conversation from stated requirements to underlying needs, and you build credibility through the depth of your understanding rather than the breadth of your pitch.
• Uncovers business drivers.
• Uncovers personal drivers.
• Surfaces constraints early.
• Aligns stakeholders.
• Asks strategic questions.
• Earns authority through depth.

What You'll Do

• Discover. Run workshops and process discovery with business, data, and engineering stakeholders.
• Structure the process and the spec.
• Architect & design. Design agentic systems end to end.
• Build. Ship working systems — agents, retrieval services, evaluation tooling, and the data flows that feed them.
• Engineer the delivery system.
• Operate (Day 2). Own what happens after launch.
• Consult. Present to and defend decisions in front of CTOs, VPs of Engineering, CDOs, and business leadership.

Qualifications

• 8–10+ years across ML, data, and software engineering.
• Python-first, production-grade (typed, tested, deployed services — not notebooks only); working proficiency in TypeScript / Node, .NET / C#, or Java is a plus.
• Track record as an ML/Data Architect, Principal Engineer, or Tech Lead.
• Has designed and owned CI/CD for AI or ML systems.
• Has put LLM and agent systems into production and kept them running.
• Deep fluency with retrieval and model behavior.
• Fluent with agentic tooling.
• Context and spec engineering.
• Day 2 experience.
• Data and integration literacy.

Requirements

• Demonstrates the discovery behaviors above.
• Runs client conversations without an account manager in the room.
• Translates technical decisions into business outcomes.
• Exceptional written and verbal communication.

Strong Plus

• Delivery in regulated environments.
• Pre-sales support.
• Classical ML in production alongside LLM work.
• Client enablement and training.
• Prior consulting or agency environment.

Work Authorization Requirements

• Applicants must be currently authorized to work in the country of this job posting on a full-time basis.
• FullStack will not sponsor applicants for work visas now or in the future.

Benefits

• Competitive pay.
• 100% remote work.
• The ability to work with leading startups and Fortune 500 companies.
• Continuing education opportunities.
• Opportunity to grow and expand your career.