Software Engineer - Infrastructure (Technical Leadership)

Meta; Menlo Park (CA); On-site; USD 271,000 - 347,000; Full time

Job summary

Meta in Menlo Park, CA, seeks an experienced Software Engineer to build AI-powered reliability systems at scale. You will prototype and ship production-ready agentic software that investigates incidents, identifies root causes, and executes mitigations under human supervision.

This leadership role blends distributed systems, AI/ML, and reliability engineering. You will mentor peers, shape architecture, and push for safe, auditable automation across Meta's infrastructure while delivering

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience.
• 12+ years of software engineering experience building large-scale distributed or infrastructure systems.
• Experience setting technical direction and leading complex engineering efforts.
• Experience applying AI or machine learning systems to production problems.
• Demonstrated experience moving concepts to production deployment and measurable impact.
• Experience diagnosing complex production systems using telemetry, code, configuration, and dependency information.
• Experience coding in languages such as C++, Java, Python, Rust, or equivalent.
• Hands-on experience building and shipping complex production systems.

Responsibilities

• Define the technical vision and architecture for agentic reliability systems across Meta.
• Design, code, and ship production agentic systems for infrastructure problems.
• Lead development of an AI agent for production incident investigation and mitigation.
• Improve agent reasoning, context, tool use, planning, evaluation, and safe execution.
• Explore techniques like fine-tuning, reinforcement learning, distillation, and inference optimization.

Skills

C++/Java/Python/Rust

Distributed systems

AI/ML in production

Incident response

Technical leadership

Mentoring engineers

Education

Bachelor's degree in CS/Engineering

Job description

Meta is seeking an experienced Software Engineer to build the next generation of AI systems for production reliability. This role sits at the intersection of large-scale distributed systems, incident response, and applied AI. You will lead the development of an AI agent that can autonomously investigate production incidents, identify likely root causes, create safe mitigation plans, and execute them while humans supervise and can intervene. You will improve the agent's accuracy, autonomy, and real-world impact, while identifying other opportunities to apply agentic systems across incident prevention, detection, mitigation, observability, and infrastructure operations. This may include improving the agent's architecture, context, and tooling, or adapting foundation models through fine-tuning, reinforcement learning, distillation, pruning, and inference optimization. This is an applied engineering role, not a research position. The ideal candidate combines deep infrastructure expertise with sound judgment about when and how to apply AI to production problems, a long-term technical vision, and the ability to move quickly from an ambitious idea to a production system operating safely at Meta scale. This is also a deeply hands-on senior IC role. You will personally prototype, build, evaluate, and ship AI systems, working directly in the code and with production data. A central challenge is creating systems that improve from experience: learning from outcomes, identifying their own failure modes, testing changes, and safely increasing their effectiveness over time.

Software Engineer - Infrastructure (Technical Leadership) Responsibilities:

• Define the technical vision and architecture for agentic reliability systems across Meta
• Personally design, code, and ship production agentic systems for complex infrastructure problems
• Lead the development of an AI agent for production incident investigation and mitigation, advancing it toward accurate, trusted, and safely supervised autonomous action
• Develop major improvements in agent reasoning, context, tool use, planning, evaluation, learning, and safe execution
• Explore and apply techniques including automated hill climbing, fine-tuning, reinforcement learning, model routing, distillation, pruning, and inference optimization, selecting the simplest approach that produces measurable gains
• Identify new high-value applications of AI across incident prevention, detection, mitigation, observability, and infrastructure operations
• Move rapidly from ambiguous problems to prototypes, validate them against real production workloads, and develop successful approaches into reliable systems at scale
• Build evaluation and experimentation systems that connect agent quality to outcomes such as investigation accuracy, successful mitigation, incident duration, and reduced operational work
• Build closed-loop improvement systems that turn production outcomes into evaluations, experiments, and better agent behavior
• Establish architectures and guardrails for production actions, including authorization, independent validation, auditability, rollback, and human oversight
• Partner with Infrastructure, AI, Product, and Reliability leaders to integrate agentic capabilities into Meta’s production ecosystem
• Influence technical strategy across organizations and mentor other engineers working on distributed systems and applied AI

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 12+ years of software engineering experience, including experience building and operating large-scale distributed or infrastructure systems
• Experience setting technical direction and leading complex, multi-year engineering efforts across organizational boundaries
• Experience applying AI or machine learning systems to production problems
• Demonstrated experience moving from technical concept to production deployment and measurable impact
• Experience diagnosing complex production systems using telemetry, code, configuration, and dependency information
• Experience coding in languages such as C++, Java, Python, Rust, or equivalent
• Recent hands-on experience building and shipping complex production systems, with the ability to move directly between architecture, experimentation, debugging, and implementation
• Experience influencing senior engineers and leaders without direct organizational authority

Preferred Qualifications:

• Experience with autonomous or semi-autonomous production actions and their safety, authorization, and rollback mechanisms
• Experience building systems that operate at hyperscale under strict reliability and latency requirements
• Experience improving agent quality through evaluation, context engineering, fine-tuning, reinforcement learning, distillation, or model-serving optimization
• Track record of identifying unconventional opportunities, rapidly prototyping solutions, and changing the technical direction of a large organization
• Deep expertise in observability, incident response, change safety, distributed systems, or production infrastructure
• Experience building self-improving or self-evolving systems, including automated experimentation, feedback loops, hill climbing, reinforcement learning, or recursive self-improvement
• Experience building production AI agents that reason across telemetry, code, configuration, deployments, and operational knowledge

About Meta:

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is proud to be an Equal Employment Opportunity and affirmatively action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [e-mail].

$271,000/year to $347,000/year + bonus + equity + benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.