Production Safety

Microsoft AI

8d • $119,800 - $261,000

About The Position

Microsoft AI is seeking a Member of Technical Staff to build, deploy, and operate production systems that ensure the safety and reliability of advanced AI products at a global scale. This role involves working on safety-critical components within the inference path, including orchestration, model- and rules-based safeguards, configuration, telemetry, fail-safe mechanisms, and rollout strategies. Additionally, the position requires building production monitoring for large-scale training and evaluation processes to maintain the health and reliability of pipelines, compute resources, and safety signals. This is an ideal role for a software engineer experienced in high-scale cloud and distributed systems, adept at balancing product safety and quality with performance metrics like latency, availability, and cost.

Requirements

• Bachelor’s degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.
• Strong software engineering skills in one or more production languages such as C++, C#, Java, Go, Rust, or Python.
• Experience designing, building, deploying, and operating distributed services or other large-scale production systems.
• Experience with containerized workloads, Kubernetes, and automated CI/CD pipelines.
• Knowledge of service reliability fundamentals, including observability, capacity planning, failure isolation, graceful degradation, and incident response.
• Ability to reason carefully about correctness, security, privacy, and failure modes in systems that affect end users.
• Ability to collaborate across engineering, machine learning, product, and policy teams and communicate system tradeoffs clearly.

Nice To Haves

• Experience with online inference platforms, model serving, API gateways, policy enforcement systems, or other latency-sensitive infrastructure.
• Experience deploying or operating machine learning models, training pipelines, or evaluation systems in production, including versioning, monitoring, failure detection, and rollback or recovery.
• Experience with Azure technologies.
• Experience with observability tooling and capacity planning.
• Familiarity with or interest in AI safety, trust and safety, abuse prevention, content moderation, security engineering, privacy, or responsible AI.

Responsibilities

• Design, build, deploy, and operate safety-critical services in the production inference path for text, multimodal, and agentic AI systems.
• Integrate model-based classifiers, policy engines, and other guardrails with model APIs and serving platforms.
• Build containerized services on Kubernetes, with automated CI/CD, staged regional rollout, rollback, and failover.
• Define and meet service-level objectives for availability, latency, throughput, correctness, and cost, including capacity planning and autoscaling.
• Build monitoring and debugging capabilities that make safety decisions and service health observable, and detect failures, stalls, and regressions in large-scale training and evaluation runs.
• Validate launches across development, staging, and production, and contribute to on-call, incident response, and root-cause analysis.
• Partner with Production Inference, Security, Privacy, Responsible AI, and product teams to resolve dependencies and meet launch requirements.
• Contribute reusable libraries, testing standards, deployment runbooks, and operational practices for safety-critical infrastructure.

Benefits

• The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year.
• There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
• Certain roles may be eligible for benefits and other compensation.
• Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Associate degree