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About the Role
We are looking for 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. You will focus on safety-critical components within the inference path, including orchestration, model and rules-based safeguards, configuration, telemetry, fail-safe mechanisms, and rollout processes. Additionally, you will develop production monitoring for large-scale training and evaluation runs to maintain the health and reliability of pipelines, compute, and safety signals. This role is ideal 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.
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 to 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.
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.
Skills
- C++
- C#
- Java
- Go
- Rust
- Python
- Kubernetes
- CI/CD
- Observability
- Capacity Planning
- Failure Isolation
- Graceful Degradation
- Incident Response
- Online Inference Platforms
- Model Serving
- API Gateways
- Policy Enforcement Systems
- Machine Learning Models
- Training Pipelines
- Evaluation Systems
- Azure
- AI Safety
- Trust and Safety
- Abuse Prevention
- Content Moderation
- Security Engineering
- Privacy
- Responsible AI
Experience Level
- Member of Technical Staff
- Software Engineering IC4
Education Level
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Salary/Compensations
- USD $119,800 - $234,700 per year (U.S. typical base pay range)
- USD $160,200 - $261,000 per year (San Francisco Bay area and New York City metropolitan area)
Benefits
- Certain roles may be eligible for benefits and other compensation.
About the Company
- Microsoft AI is building AI systems and products that empower people’s lives.
- Our work is driven by a community of brilliant, interdisciplinary minds working across frontier model development, product engineering, and responsible AI.
- Within Microsoft AI, the Safety team develops the training methods, evaluations, runtime safeguards, monitoring, and infrastructure needed to make advanced AI systems safer, more reliable, and more useful.
- Our work spans text, multimodal, and agentic systems and is developed in close partnership with other Research teams, Production Inference, Security, Responsible AI, Microsoft product organizations, and external partners and customers.
Equal Opportunity
- Microsoft is an equal opportunity employer.
- All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances.
- If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.