Datadog’s CodeGen team builds systems that use AI to read, understand, generate, and safely change real code — powering automated fixes, CI/PR automation, agentic remediation, and Infrastructure-as-Code workflows. The team ties code understanding to observability so assistants can explain problems and produce safe, auditable code changes.
We’re a new team building AI-assisted tools to make Datadog developers more effective, by autonomously generating tests, fixing bugs, and improving performance.
We’re looking for a product-minded generalist to help us quickly define and ship products that make all Datadog customers 10x developers.
At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.
What You’ll Do:
- Lead a team of engineers responsible for building production systems that enable code understanding and automated code changes — from parsers and telemetry ingestion to model serving, evaluation, and PR automation.
- Drive technical direction and execution: set a clear roadmap, prioritize work, remove blockers, and raise quality and reliability bar for codegen features (safety, correctness, performance).
- Partner with product, applied research, infra/SRE, security, and other engineering teams to ship end-to-end experiences that safely apply model outputs (PRs, CI checks, automated apply flows).
- Build and maintain robust evaluation and monitoring pipelines (offline and online) to measure model quality, drift, and downstream correctness of code changes.
- Own hiring, performance development, 1:1s, and career growth for your reports; grow a high-performing, inclusive team.
- Be accountable for production readiness: on-call expectations, postmortems, SLIs/SLOs, and operational playbooks for codegen services.
- Maintain engineering rigor around data pipelines, model inputs, determinism, reproducibility, and reproducible CI/CD for model + infra changes.
Who You Are:
- Proven experience in software engineering and applied science, with a focus on engineering LLM-based systems in production
- Demonstrated experience managing small teams of software engineers and/or applied scientists, with a track record of delivering high-quality products
- Strong software development skills and proficiency in Python and Go
- Strong understanding of machine learning theory, statistics, and fundamentals
- Excellent communication abilities to convey complex technical concepts clearly
- A collaborative mindset and proven experience in working in cross-functional teams
- A proactive approach with a passion for continuous learning and innovation
- Demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI