Principal Full Stack Engineer - AI Systems & Engineering Automation

• Design the automation layer. Create and refine the skills, rules, context packages, and self-verification harnesses that enable coding agents to plan, implement, test, and deliver production-quality software with minimal human involvement - and make that involvement trend toward zero over time.
• Run parallel agent operations. Dispatch concurrent workstreams to agent fleets, validate outputs against enterprise-grade criteria, and treat every agent failure as a system-design problem to solve once and permanently.
• Deliver customer-facing features at startup speed. Collaborate shoulder-to-shoulder with product leadership in rapid cycles - a customer insight from a morning call can ship as a polished feature the same day. Velocity is non-negotiable, but so is reliability; these customers stake their brand reputation on our platform.
• Compound gains across the team. Every rule tuned, every eval refined, every context file improved gets packaged and shared - your work lifts the ceiling for every engineer and every agent on the team, not just your own throughput.
• Set technical direction. Scope initiatives, review architecture and PRs, mentor senior engineers, and enforce quality standards. You model the AI-native engineering culture and hold the bar before anything reaches production.

We’re looking for a Principal Full Stack Engineer who obsesses over engineering leverage: someone who sees a repeatable task and immediately thinks about the scaffolding, context, and evaluation loop that would let an agent handle it permanently. You won’t be measured on lines written - you’ll be measured on how much of the development lifecycle you’ve made autonomous, reliable, and shared., * 5+ years of production full-stack engineering on web-based systems - real depth in both front-end and back-end - with demonstrated experience stepping into tech lead or staff-level roles directing other senior engineers.

• An AI-native operating model. You don’t hand-code or pair-program with a chatbot. Your instinct is to build the context, tooling, and guardrails that let agents own work end-to-end, then review and verify the result. You think in systems, not keystrokes.
• Broad, deep tool fluency at the frontier. You’re a power user of leading agentic development tools (Claude Code, Cursor, Codex, or peers) - and you actively benchmark new tools and models weekly. Being locked into a single tool is a liability; never having gone deep on any is equally disqualifying.
• Current, nuanced model judgment. You can explain which frontier model to reach for in a given scenario, what changed in the last release cycle, and when to trade capability for cost or latency - because you’ve tested them yourself.
• Strong product instinct. Hand you a goal and you’ll define the solution, ship it polished, and own it through to enterprise release - defensive coding, edge-case handling, security, and automated evaluation included. “Demo works” is never your finish line.
• Cloud & CI/CD ownership. Enough AWS and pipeline experience to stand up, ship, and operate a product solo - no infrastructure hand-offs required.
• Production LLM experience. You’ve shipped real applications integrating large language models via APIs, prompt engineering, agent pipelines, or automation workflows.
• Model Context Protocol (MCP) - hands-on understanding and prior application.

Bonus Points

• Experience with enterprise social, community, or customer-engagement platforms.
• Contributions - published writing, talks, or open source - in agentic engineering or AI-assisted development.
• Hands-on design of multi-agent orchestration: parallel execution, worktree strategies, or file-based agent coordination.
• A track record of building reusable internal tooling (shared rules, eval frameworks, skill libraries) that measurably accelerated a team’s output.

• Uncapped AI resources. No token budgets, no tool restrictions. If a superior model or configuration exists, the door is open - always.
• Fully remote, async-first, worldwide. Written artifacts over status meetings, deep focus on your own schedule, and a feedback loop fast enough to close the gap between idea and production in hours.
• Outsized influence in a lean team. Weekly outcome cycles, direct access to product leadership, and Fortune 100 customers who feel the impact of your decisions immediately.
• Career-defining skill development. You’ll build rare expertise at the intersection of applied AI systems, agent orchestration, and enterprise product engineering - the discipline that compounds fastest as AI capabilities accelerate.

If your career has been building toward this moment - where engineering excellence means designing the system that lets AI deliver, not just delivering yourself - we should talk.