[Hiring] Forward Deployed 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:
• 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.
• 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, data, and engineering stakeholders. Assess data readiness honestly. Separate genuine AI problems from workflow problems wearing an AI costume.
• Structure the process and the spec: For any business process being automated, map the current state, decision points, data inputs, 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 with emphasis on context and retrieval architecture — data sourcing, chunking, embeddings, hybrid search, reranking, permissions-aware retrieval, knowledge graphs where warranted — plus orchestration, MCP/tool integration, guardrails, and human-in-the-loop checkpoints.
• Build: Ship working systems — agents, retrieval services, evaluation tooling, and the data flows that feed them. Prototypes that prove value in weeks, not slideware.
• Engineer the delivery system: Own CI/CD for what you build, extended to AI: prompt and context versioning, eval suites that run in the pipeline and gate releases.
• Operate (Day 2): Own what happens after launch — eval harnesses, groundedness and retrieval metrics, observability and tracing, cost and latency management, drift, and the handoff that lets the client’s team run it without you.
• Consult: Present to and defend decisions in front of CTOs, VPs of Engineering, CDOs, and business leadership. Quantify impact in their terms. Support pre-sales scoping and proposal work when the deal calls for it.

Qualifications

• 5+ years of professional software development experience with core proficiency in Python (or TypeScript/Node.js).
• Has shipped at least one agentic AI solution, LLM workflow, or RAG architecture to a production environment.
• Advanced English is required.
• Successful completion of a four-year college degree is required.
• Demonstrated hands-on experience using AI developer tools (such as Cursor, Claude Code, Gemini CLI, or OpenAI Codex) in daily workflows.
• Track record of leading client-facing discovery calls to translate unstructured business requirements into technical architectures.
• Hands-on experience designing and integrating RESTful APIs, microservices, or event-driven architectures.
• Experience building agentic systems using orchestration frameworks or APIs such as LangGraph, LangChain, n8n, Model Context Protocol (MCP), or direct LLM APIs.
• Proven experience taking full end-to-end technical ownership of features from discovery to deployment.
• Ability to work through new and difficult issues and contribute to libraries as needed.
• Ability to create and maintain continuous integration and delivery of applications.
• Forensic attention to detail.
• A positive mindset and a can-do attitude.
• Experience working on Agile / Scrum teams.
• Meaningful experience working on large, complex systems.
• Ability to take extreme ownership over your work.
• Ability to identify with the goals of FullStack's clients, and dedicate yourself to delivering on the commitments you and your team make to them.

Strong Plus

• Production AI operations (Day 2): eval harnesses, observability and tracing, cost and token economics, drift, debugging non-deterministic systems.
• Prompt- and eval-level regression testing running in CI and gating releases.
• Delivery in regulated environments (financial services, healthcare, insurance, manufacturing).
• Pre-sales support: discovery calls, SOW and estimate shaping, technical proposal defense.
• Process mining, operations analysis, or transformation consulting background.
• Client enablement and training — building the client team’s capability, not just the system.
• Prior consulting or agency environment; comfort with ambiguity and multiple accounts.

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.