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You will lead a high-output engineering pod to migrate AWS Lambda applications to Azure by designing robust agentic scaffolding and feedback loops. Your role involves balancing hands-on harness development with guiding the team to ensure agent-generated code remains coherent and reliable.
This is a remote position.
Need to have experience in handling big teams.
You will lead a small, high-output agentic engineering pod migrating AWS Lambda applications to Azure.
Inspired by OpenAI’s Harness Engineering model, your primary job is not writing code — it is designing the harness: the scaffolding, constraints, and feedback loops that let Claude Code agents to do reliable work.
You own the claude_code_forge scaffolding, define CLAUDE.md specs, enforce architectural
invariants, and build the CI/CD guard-rails that keep agent-generated code coherent.
You are a player-coach: 70% building harness, 30% guiding the pod.
Own and evolve the claude_code_forge scaffolding — repo structure, CLAUDE.md templates, creating agents, MCP tool configs, and custom slash commands
Decompose the AWS estate into depth-first migration work-packages with clear acceptance criteria agents can validate
Enforce architecture mechanically (structural tests, linting rules, dependency-layer checks) rather than through documentation alone
Run weekly entropy-management sweeps using background Claude Code tasks to maintain codebase coherence
Mentor engineers on prompt-driven TDD, multi-agent orchestration, and Claude Desktop / Cowork workflows
Report migration velocity, agent utilisation, and risk to stakeholders You Bring
6-8 years software engineering; 2+ years leading delivery teams
Deep AWS and Azure serverless experience (Lambda → Functions, DynamoDB → Cosmos DB, Step Functions → Durable Functions)
Hands-on Claude Code, Claude Desktop, and Cowork proficiency
Track record of building developer tooling, CI/CD pipelines, or platform engineering
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