AI Product Engineer / Forward Deployed Engineer
Role Description
Remote (North America; San Francisco or Austin preferred) · Full-time
Compensation: $140K–$180K base + competitive equity
About the Company
Our client is an early-stage, venture-backed AI infrastructure company that helps enterprises trust their voice AI agents. Their platform covers testing before launch, adversarial stress-testing, and monitoring of live calls in production. They already serve enterprise customers in regulated industries such as healthcare, financial services, and telecom, and revenue has grown quickly over the past year.
Early stage · ~15 people · Industry: AI, Developer Tools, B2B, Enterprise
The Role
We're looking for an early-career engineer who wants to split their time between building product and working directly with customers. You'll sit with the technical teams who use the platform, figure out what they actually need, and then build and ship it yourself. The team ships several times a day, the founder still writes code, and there are no handoffs between the person who hears the problem and the person who solves it.
What you'll be doing
Working closely with enterprise engineering teams to uncover gaps, then scoping and shipping the fix yourself
Taking features from first conversation through prototype, launch, and iteration, across both frontend and backend
Acting as a hands-on technical partner during pilots and after the sale
Turning one-off customer solutions into reusable parts of the platform
Using AI coding tools as a normal part of how you build, so you can move at startup speed
Tech stack: TypeScript, Python, React, Next.js, Node.js, Tailwind, OpenAI, Anthropic, Cursor, Codex, LiveKit, WebSockets, Pipecat, Temporal, AWS, Kubernetes, PostgreSQL, Redis, Terraform, OpenTelemetry, Figma, Vapi, Retell AI, ElevenLabs
Requirements
Up to about 3 years of experience in a role that mixes coding with customer contact, such as product engineering, forward deployed engineering, solutions architecture, or running your own startup
Somet...
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About Forward Deployed Engineering
Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.
Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.
Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.
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