Role Description
FDEs at CVP are the rare engineers who get to do all of it — build, integrate, and open doors — and see the full arc of impact from a single deployment. You design the solution, wire the integrations, ship production code, and then watch a real agency change how it operates because of what you built. When that works, it creates the next opportunity: your technical reputation *is* the growth motion. Engineers who thrive here want to own outcomes, not hand them off.
You may be in an agency briefing one hour and debugging a container the next, shifting contexts without losing signal. You treat ambiguity as raw material — undefined problems aren't blockers, they're where the work starts. You surface requirements by asking the right questions, not by waiting for a spec. And when it's time to communicate, you write with the kind of precision that makes technical updates actually land with non-technical stakeholders.
Fifer is our flagship enterprise GenAI platform: deployed entirely within agency cloud environments, zero data leaving premises, swappable LLMs, and multi-agent RAG. When agencies want to build AI-powered workflows, audit processes, expert assistants, or developer tooling, you are how that happens. You’ll extend Fifer through custom skills, MCP server integrations, and agent workflows built specifically for each customer’s mission.
This role requires the ability to obtain a Public Trust clearance
Build
- Own technical delivery from discovery through production across multiple concurrent agency deployments
- Write and ship production-grade integrations using Fifer’s APIs, modern web frameworks, and backend services
- Build custom skills, agent configurations, and MCP server integrations that extend Fifer to customer-specific missions
- Deploy and configure FiferAUDIT in customer cloud environments (AWS, Azure, GCP) ensuring FedRAMP compliance boundaries are met
Embed
- Work alongside agency technical teams and end users to understand workflows from the source, not requirements docs
- Run discovery sessions, technical workshops, and working sessions that translate mission need into engineered solutions
- Guide and train customers on prompt engineering, agent design, and agentic workflow optimization to maximize mission impact
Influence
- Partner directly with prospective and current agency clients as a technical advisor, conducting discovery sessions to uncover operational pain points, then rapidly prototyping and deploying tailored AI solutions that demonstrate immediate, tangible value
- Build and maintain deep relationships with customer technical leadership and program stakeholders
- Travel up to 50% to customer sites (primarily DC area) for on-site implementation, workshops, and relationship building
Required
- 5+ years of software engineering experience shipping production systems
- Full-stack proficiency: JavaScript/TypeScript and/or Python; you can own a feature end to end
- Cloud deployment experience (AWS, Azure, or GCP); comfortable with Kubernetes, Docker, Terraform, and CI/CD pipelines
- Hands-on experience building or integrating LLM/GenAI-powered systems. You understand how model behavior, context windows, and retrieval quality affect what users experience
- Expertise with AI agent harnesses (OpenCode, Pi, Claude Code, Cursor, Codex or similar) and practical experience building agent configurations and skills
- Strong Linux system administration — you can install, configure, and debug on VMs and Kubernetes clusters without a runbook
Preferred
- Prior FDE, deployment engineering, or solutions engineering experience at a commercial product company
- Experience working with federal civilian agencies (HHS, CMS, DHS, VA, DOL, or similar)
- Experience with FedRAMP-compliant deployments
- RAG architecture and LLM operations knowledge (prompt engineering, retrieval tuning, model evaluation, evals)
- MCP (Model Context Protocol) server development experience
- PostgreSQL and schema design experience
- Active Public Trust clearance or higher
How We Hire
After submitting your application, you’ll receive a challenge brief: a real compliance or government workflow problem, and a few days to build something small and working using Fifer or comparable AI tools. We want to see how you think from first principles and how you work alongside AI as a development partner.
Skip the cover letter. Your GitHub and your submission speak for themselves.
About CVP
CVP is an award-winning healthcare and next-gen technology and consulting services firm solving critical problems for healthcare, national security, and public sector clients. We help organizations achieve lasting transformation.
CVP is an Equal Opportunity Employer dedicated to actively recruiting individuals and providing advancement opportunities based on merit and legitimate job qualifications. We ensure that all associates receive equal opportunities based on their personal qualifications and job requirements. CVP strictly prohibits any form of discrimination or harassment.
At CVP, we cultivate a work environment that encourages fairness, teamwork, and respect among all associated. We are committed to maintaining a workplace where everyone can grow both personally and professionally.
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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