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We’re building AI‑first engineering systems that power growth at Microsoft — designing, shipping, and scaling code that directly shapes how millions of developers experience and adopt AI. As a Growth Engineer in CoreAI, you’ll sit at the intersection of product, engineering, and data, driving experimentation, learning velocity, and real business impact across world‑class developer and AI products. This role is about shipping fast, learning faster, and scaling what works — all while upholding Microsoft’s commitment to responsible, inclusive, and trustworthy AI.
Job Responsibility:
Own growth through engineering excellence and experimentation
Design, ship, and iterate on growth experiments across acquisition, activation, engagement, and retention
Build and evolve A/B testing frameworks, metrics, and tooling that raise experimentation quality and confidence
Partner closely with Product, Data Science, Design, and Research to turn hypotheses into shipped learnings
Use data and telemetry to guide decisions — from experiment design to rollout strategy
Scale successful growth patterns across high‑traffic, global AI products
Balance speed and rigor in a fast‑paced, AI‑first engineering environment
Requirements:
Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
Nice to have:
2+ years shipping A/B tests end‑to‑end in production (design → instrumentation → analysis → rollout), including improving experiment quality and guardrails
4+ years building and shipping high‑availability features for multi‑region, globally distributed systems (resiliency, failover, capacity planning)
Demonstrated experience leaning heavily on AI to accelerate engineering velocity, including using AI tools to prototype, implement, debug, and iterate on production features