Forward Deployed Engineer

NimbleWay•New York, NY

3d•$170,000 - $235,000•Hybrid

About The Position

This is Nimble’s founding Forward Deployed Engineer role. You will build AI agents and search integrations with customers and take them into production. After qualification, you will work with the Solution Consultant and customer engineers to refine the architecture and agree on success criteria. You will build an initial working version using the customer’s real queries, workflows, and codebase, evaluate it against the customer’s test set, and lead implementation through production deployment and handoff. You will equip customer engineers to operate and extend the solutions. A typical engagement lasts 12 weeks. You will own technical decisions for each engagement, including implementation architecture, orchestration approach, evaluation design, technical scope and sequencing, and determining what can be reused versus what must remain customer-specific. As the first member of the FDE team, you will also help shape the function’s strategy, engagement model, playbook, and hiring plans. The role is based in New York or San Francisco, with three days per week in the office. It reports to the Director of Solution Consulting and carries no sales quota.

Requirements

Write production Python and be able to read and modify TypeScript.
Have shipped and operated LLM-powered applications for real users, and be able to explain how failures, latency, and cost were managed.
Have designed or improved evaluations for an LLM or other nondeterministic system and used results to guide engineering decisions.
Have built tools for agents to call through MCP, function calling, or an equivalent approach.
Have at least 4 years of software engineering experience.
Be able to show shipped LLM or agent work, such as a repository, live product, or case study.
Have worked directly with customers or external partners to scope and deliver technical projects.
Be able to lead a discovery call with a VP and debug a failing run with an engineer.
Be comfortable with ambiguity and rapid change in a fast-paced startup.

Nice To Haves

Experience with retrieval and RAG, including hybrid search, reranking, and freshness.
Experience building with LangGraph, the OpenAI Agents SDK, the Vercel AI SDK, or the Claude Agent SDK.
Experience delivering data to Snowflake or Databricks.
Experience with web data, including scraping, anti-bot systems, and structured extraction.
Effective use of AI development tools, with responsibility for reviewing, testing, and maintaining generated code.

Responsibilities

Turn customer goals into working flows of Search, Extract, and Web Search Agent calls integrated with the customer’s code.
Build the first version using the customer’s real queries, working alongside the customer’s engineer.
Define representative evaluation sets and success criteria with customers; benchmark quality, latency, and cost; and instrument production workflows to detect failures and regressions.
Write orchestration code for stable production workflows, including fan-out, deduplication, retries, and cost caps.
Integrate Nimble into customer agents through its MCP server, SDKs, or API, on a schedule or on demand.
Present results to customer engineers and executives, and document the technical win with the Solution Consultant.
Write runbooks, train customer engineers, and hand accounts over to Customer Success.
Identify recurring customer needs and turn successful implementations into reusable integrations, evaluation tools, reference applications, and product improvements.
Shape the FDE function, including its engagement model, entry and exit criteria, playbook, and future hiring profile.
Own technical decisions for engagements, including architecture, orchestration, evaluations, scope, sequencing, and reuse versus customer-specific implementation.