Forward Deployed Engineer (TypeScript + AI) - Remote - USA

About FullStack FullStack is your AI-native engineering partner, built to turn AI capability into certainty. Most companies can demo AI; few can get it to production and prove what it produced. We close that gap with three capabilities, AI built into your products from the start, elite vetted talent who apply it, and transparent execution that shows value every step of the way. With now over 600 customers in North America, FullStack is one integrated partner for all your AI engineering needs. With FullStack, you move forward with confidence.

We’re Most Proud Of

• Offering life-changing career opportunities to talented software professionals across the Americas.
• Building highly-skilled software development teams for hundreds of the world’s greatest companies.
• Having delivered hundreds of successful custom software solutions, which have positively impacted the lives and careers of millions of users.
• Our 4.1-star rating on GlassDoor.
• Our client Net Promoter Score of 68, twice the industry average.

The Position 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 make it hold up in the real environment.

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 debugging why an agent’s tool-calling loop degraded after a context change. 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 application engineering: you make agents real inside the client’s actual systems, workflows, and delivery pipelines.

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. What outcome matters, what it’s worth, why now, and what happens if nothing changes.
• Uncovers personal drivers. What each stakeholder is measured on, what they’re worried about, and what a win looks like for them individually.
• Surfaces constraints early. Security, compliance, data access, budget, skills, politics, timelines — the things that kill projects in month two.
• Aligns stakeholders. Spots conflicting goals between business, engineering, and risk, and brings them to a shared definition of success.
• Asks strategic questions. Follows the answer with “why,” “how do you know,” and “what happens today when…” — without interrogating. Clients leave the conversation understanding their own problem better.
• Earns authority through depth. Credibility comes from the quality of the questions and the insight in the playback, not from pitching technology.

What You’ll Do

• Discover. Run workshops and process discovery with business and engineering stakeholders. Separate genuine AI problems from workflow problems wearing an AI costume. Come back with a scoped, defensible point of view.
• Structure the process and the spec. For any business or engineering process being automated, map the current state, decision points, and exceptions, then turn it into specifications that both people and AI systems can execute against reliably.
• Architect & design. Design agentic systems end to end — orchestration, context and retrieval architecture, tool and MCP integration, guardrails, human-in-the-loop checkpo…