Principal Forward Deployed Engineer

Responsibilities

• Embed with IT and business teams on priority SPE projects and ship full applications end to end (data layer, backend services, AI integration where the application needs it, user-facing surface), using AI-DLC to compress the development cycle dramatically.
• Lead AI-DLC adoption in your partner teams: coach the team into team-tier self-sufficiency on AI-assisted development so they continue using the practice after you roll off.
• When the application requires inference at runtime, build production LLM components on the EIP platform (RAG, agentic orchestration, prompt architecture, evaluation frameworks, observability, and guardrails).
• Work directly with non-technical business stakeholders, from frontline operators and analysts through senior executives, to draw out what they actually need, shape a solution together, and translate it into a decomposed, shippable plan in real time.
• Harvest reusable patterns from every engagement back into the EIP platform backlog so what you build becomes platform capability and successive engagements compound.
• Hold the line with senior stakeholders when the request needs to change, and own what you ship through the handoff to the incumbent application team.

Qualifications

• Full-stack production engineering experience across the whole application stack: object-oriented development proficiency, backend services, data pipelines, user-facing application surfaces (web UIs, internal tools, integrations), cloud (AWS and / or Azure), containers, and infrastructure-as-code. You ship every layer, not just the AI components.
• Hands-on experience using AI-assisted development tooling (Claude Code, Cursor, GitHub Copilot, Windsurf, or equivalent) to ship production code at meaningfully faster cycle times than traditional development.
• Comfort generating, reviewing, and iterating on AI-generated code at velocity, with the judgment to know what to keep and what to throw away.
• 8+ years of professional software engineering experience.
• Some production experience with LLM-based systems (RAG, agents, prompt architecture, evaluation frameworks), applicable to the subset of engagements where the application includes runtime AI.
• Comfort operating with high autonomy in ambiguous, fast-moving engagements. You write, ship, and own production code; you do not hand off recommendations.
• Bachelor's degree or equivalent practical experience.