Identify modernization opportunities and drive them from discovery to delivery, aligning priorities with partner teams.
Build LLM-powered pipelines for code understanding, migration planning, large-scale refactoring, and validation.
Run multiple agent-driven workstreams across projects concurrently, managing context, dependencies, failures, and integration.
Connect agents to source code, compilers, build systems, tests, and diagnostics.
Automate change/test/diagnose/correct loops, with clear stopping conditions and targeted human review.
Divide migrations into independently verifiable units, preserving behavior and numerical equivalence where required.
Replace recurring manual work with reusable tools, including automation that reduces your own supervision burden.
Evaluate and adopt emerging tools quickly when they improve quality, throughput, reliability, or cost.
Deliver integrated code, documented workflows, and a practical handover to product teams.
Required Qualifications:
Strong software development experience with ownership of production systems and complex existing codebases.
Demonstrated self-directed delivery: you have defined and solved underspecified problems without step-by-step supervision.
Hands-on LLM or coding-agent experience beyond code completion, with concrete examples of useful automation.
Experience building developer tools, pipelines, or integrations that multiply engineering output.
Ability to decompose large problems, delegate parallel tasks, and integrate results against measurable acceptance criteria.
Strong testing, debugging, architecture, performance, and failure-analysis fundamentals; judgment about when human intervention is necessary.
Entrepreneurial ownership: prioritize valuable work, make pragmatic tradeoffs, remove obstacles, and follow through to adoption.
Ability to learn unfamiliar tools quickly, adapt workflows as capabilities evolve, and communicate clearly across teams.
Production work, internal tools, open-source contributions, and substantial personal projects all count. Show what you built, what it automated, and how you established that it worked - not just which AI tools you used.
Preferred Qualifications:
Experience with large-scale refactoring, legacy modernization, or cross-language migration.
Experience with Rust, C++, C, or Fortran.
Experience building multi-agent workflows or integrating LLM APIs with development tools.
Background in CI/CD, automated testing, benchmarking, observability, or validation tooling.
Experience with scientific, mathematical, engineering, or simulation software where correctness is critical.
Familiarity with cloud platforms and distributed systems where relevant to modernization.
Responsibilities
Identify modernization opportunities and drive them from discovery to delivery, aligning priorities with partner teams.
Build LLM-powered pipelines for code understanding, migration planning, large-scale refactoring, and validation.
Run multiple agent-driven workstreams across projects concurrently, managing context, dependencies, failures, and integration.
Connect agents to source code, compilers, build systems, tests, and diagnostics.
Automate change/test/diagnose/correct loops, with clear stopping conditions and targeted human review.
Divide migrations into independently verifiable units, preserving behavior and numerical equivalence where required.
Replace recurring manual work with reusable tools, including automation that reduces your own supervision burden.
Evaluate and adopt emerging tools quickly when they improve quality, throughput, reliability, or cost.
Deliver integrated code, documented workflows, and a practical handover to product teams.
Required Qualifications:
Strong software development experience with ownership of production systems and complex existing codebases.
Demonstrated self-directed delivery: you have defined and solved underspecified problems without step-by-step supervision.
Hands-on LLM or coding-agent experience beyond code completion, with concrete examples of useful automation.
Experience building developer tools, pipelines, or integrations that multiply engineering output.
Ability to decompose large problems, delegate parallel tasks, and integrate results against measurable acceptance criteria.
Strong testing, debugging, architecture, performance, and failure-analysis fundamentals; judgment about when human intervention is necessary.
Entrepreneurial ownership: prioritize valuable work, make pragmatic tradeoffs, remove obstacles, and follow through to adoption.
Ability to learn unfamiliar tools quickly, adapt workflows as capabilities evolve, and communicate clearly across teams.
Production work, internal tools, open-source contributions, and substantial personal projects all count. Show what you built, what it automated, and how you established that it worked - not just which AI tools you used.
Preferred Qualifications:
Experience with large-scale refactoring, legacy modernization, or cross-language migration.
Experience with Rust, C++, C, or Fortran.
Experience building multi-agent workflows or integrating LLM APIs with development tools.
Background in CI/CD, automated testing, benchmarking, observability, or validation tooling.
Experience with scientific, mathematical, engineering, or simulation software where correctness is critical.
Familiarity with cloud platforms and distributed systems where relevant to modernization.
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