Role Description
The Role
We're looking for a technically strong, customer-focused Forward Deployed Engineer to help enterprise customers build and scale Agentic AI — from first conversation to production.
What You'll Do
- Be the technical partner for customers, driving deployments from ideation to production.
- Translate customer problems into clear requirements (PRDs, workflows, success criteria) and build them.
- Collaborate with Product, Engineering, and Solutions teams to build platform features.
What We're Looking For
- 2+ years as a Forward Deployed Engineer or software engineer — startup experience preferred; founder or founding engineer background is a plus.
- Proficiency in at least one language: Python, Go, JavaScript, or similar.
- Ability to proactively surface customer challenges during onboarding.
- End-to-end ownership mindset — you figure out what you don't know and get it done.
- A humble, collaborative attitude with a high-output, multi-project operating style.
Details
Hybrid (2 days/week in Palo Alto). Bay Area based.
Base salary: $130,000–$160,000, plus equity and benefits.
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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