Forward Deployed Engineer

San Francisco · New York · Remote · 2+ years experience · Full-time · Posted Oct 6, 2026

At a glance

The Forward Deployed Engineer embeds directly with customer teams to own outcomes and ship production-grade AI systems.
This role serves as a critical technical feedback loop, bridging the gap between field requirements and product engineering.
You will manage projects end-to-end, from initial discovery and architecture to production rollout and post-launch support.

Lead discovery with customers to identify bottlenecks and define success metrics.
Design and ship production agents, AI applications, and coding-agent workflows.
Get initial versions live quickly and harden them through iteration and monitoring.
Own production quality, including tracing, evals, debugging, and managing latency/cost tradeoffs.
Build systems around models, including tools, MCP servers, retrieval, and CI gates.
Integrate solutions into customer auth, data, workflow, and delivery systems.
Measure outcomes such as revenue, cost, hours saved, and cycle time.
Work directly with Staff+, platform, and domain leaders to communicate tradeoffs.
Enable customer teams to operate built systems and document reusable patterns.

5+ years of experience in software engineering, machine learning engineering, or data science.
Ability to write and review production code in Python, JavaScript, or TypeScript.
Proven experience owning a customer or operator outcome from problem to shipped system.
Experience building and owning AI-native workflows or agents in production.
Experience debugging production failures related to models, tools, data, or pipelines.
Experience handling production reliability, including metrics, alerts, and safe rollouts.
Ability to build end-to-end, covering frontend, backend, infra, and prompt iteration.
Ability to thrive in ambiguity without needing a complete spec.
Strong communication skills for interacting with both working engineers and VPs.

2+ years in a customer-facing role leading discovery and accountability for external stakeholders.
Hands-on depth in agents and tool-calling.
Experience with eval harnesses.
Experience with retrieval and context systems.
Experience with CI/CD or developer platforms.
Experience with AI-native coding workflows in a real repo.
Experience as a forward-deployed, solutions, or platform engineer embedded with customers.
Experience as a founding engineer who owned an AI product end to end.