Role Description
- Arlington, Virginia, United States
Location: Arlington, VA or New York City
Work Model: Hybrid
Compensation: $160,000 to $200,000 base + equity
Overview
An early-stage software company operating in stealth is building advanced systems for complex, high-consequence government environments. The engineering team is small, and each engineer carries meaningful influence over both customer outcomes and product direction.
This role sits at the boundary between production engineering and the end user. The engineer will take ambiguous operational problems directly from customers, decide what should actually be built, prototype quickly, and own technical delivery through deployment in live environments. The work includes the unglamorous integration and hardening required to make software run reliably where it matters.
This position suits engineers who want ownership of a problem from first conversation to fielded capability and are comfortable being both the technical point of contact and the person writing the code.
What You’ll Do
- Work directly with customers to understand complex workflows, technical constraints, and capability gaps
- Translate ambiguous operational requirements into clear technical solutions
- Build and ship full-stack software prototypes from concept through deployment
- Own technical projects end-to-end, including the less polished work needed to get software functioning reliably in real customer environments
- Rapidly evaluate ideas and determine which should become durable products versus short-term prototypes
- Bring customer feedback and technical learnings back to the engineering team to shape product direction
- Serve as the technical point of contact for customers while remaining a hands-on engineer
What We’re Looking For
- 2+ years of experience writing production software
- Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, Physics, or a related technical field, or equivalent professional experience
- Strong software engineering fundamentals: the ability to write, debug, and maintain production-quality code
- Ability to work independently through ambiguous technical problems without a detailed specification
- Sound technical judgment and the ability to quickly determine what is and is not worth building
- Clear communication skills and comfort working with both technical and nontechnical users
- Full understanding and ownership of the code you ship, including without reliance on AI-assisted development tools
- U.S. citizenship required for security clearance eligibility
Preferred
- Experience delivering software directly to government, defense, or other operational customers
- Active Secret or Top Secret clearance
- Experience with TypeScript, React, and/or Python
- Demonstrated ability to rapidly build and deploy functional full-stack applications
- Prior experience at an early-stage startup or similarly high-ownership engineering environment
- Open-source contributions, side projects, or other evidence of building outside of a primary job
Compensation
$160,000 to $200,000 base salary plus equity, depending on experience and qualifications. Competitive benefits are provided.
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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