Manager I, Engineering- CodeGen

Details

• 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.
• 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-generated output
• You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• Intradepartmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
• Access to Inclusion Talks, our internal panel discussions
• Free, global mental health benefits for employees and dependents age 6+
• Competitive global benefits