Manager , Engineering - CodeGen

Datadog’s Code Gen 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‑mindful 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.

• 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 the 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, SLI/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.

• 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.

#LI-Hybrid

Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate’s skills, qualifications, and experience. In addition, Datadog offers a wide range of best‑in‑class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.

The reasonably estimated yearly salary for this role at Datadog is: $187,000 – $240,000 USD.

Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers,…