Staff AI Developer Productivity Engineer

Polygon Labs

4d•Remote

About The Position

Polygon Labs is a software development company building and developing a network of aggregated blockchains via the Agglayer, secured by Ethereum. As public infrastructure, the Agglayer will bring together user bases and liquidity for any connected chain, and leverage Ethereum as a settlement layer. Polygon Labs has also contributed to the core development of several widely-adopted scaling protocols and tools for launching blockchains, including Agglayer CDK, Polygon PoS & Katana. We’re looking for a staff-level, hands-on engineer at the intersection of Developer Productivity, DevEx, and AI to make our engineering organization more effective. In this role, you’ll identify bottlenecks across the developer lifecycle (planning → coding → review → testing → release → incident response → onboarding) and build internal tools and agentic workflows that measurably improve delivery speed and quality. You’ll operate with an AI-first mindset: rapidly experiment with the latest coding agents and AI workflow patterns to see what’s possible today, forecast what’s likely to become viable in the next 3–6 months, and pragmatically fall back to conventional tooling when AI isn’t the right fit. You’ll own discovery, roadmap, and backlog end-to-end, run short data-driven trials, and productionize what works. You’ll work closely with the CTO, Engineering, DevOps/Infrastructure, Security, and Product to ensure everything integrates cleanly into existing workflows and raises the bar on quality, not just speed.

Requirements

5+ years of experience building internal tooling, developer platforms, or CI/CD automation.
Proven experience integrating LLMs into workflows with prompting, retrieval, and quality evaluation.
Familiarity with structured/agentic workflows and tool-use protocols like MCP or equivalents.
Strong understanding of CI/CD, test strategy, and quality tooling for reliable, fast engineering loops.
Product-thinking mindset with a track record of driving measurable dev productivity improvements.
Excellent cross-functional communication skills; comfort enabling change through docs, demos, and async channels.

Nice To Haves

Experience rolling out AI coding tools (e.g., Claude, Codex, Copilot) with org-wide standards and adoption frameworks.
Strong evaluation skills for LLM output (rubrics, golden tasks, human-in-the-loop reviews).
Background in large-scale code migrations or refactors using AST-based automation.
Familiarity with observability practices for developer platforms and performance tuning AI workloads.
Experience in regulated or high-integrity domains where safety, correctness, and auditability are critical.

Responsibilities

Design and implement agentic workflows for requirements clarification, planning, PR generation, and refinement, with human-in-the-loop and safety gates by default.
Develop internal tools across IDEs, GitHub, Slack, and web apps to accelerate the SDLC and create consistent “golden paths.”
Build and maintain integrations with internal systems (CI, docs, metrics, task trackers) to enable context-rich agent behavior.
Automate high-leverage workflows like refactors, scaffolding, test generation, and documentation updates with LLM and AST-based tools.
Lead discovery and roadmap definition through engineer interviews, telemetry, and measurable outcome setting.
Drive adoption via enablement programs—playbooks, office hours, prompts—and ensure agentic workflows become default.
Maintain operational excellence: tool monitoring, versioning, support, and deprecation processes.