Software Engineer - Infrastructure (Technical Leadership)

Meta; New York (NY); Sur place; USD 271 000 - 347 000; Plein temps

Résumé du poste

Meta seeks an experienced Software Engineer to build AI systems for production reliability. This role sits at the intersection of large-scale distributed systems, incident response, and applied AI.

You will lead an AI agent that autonomously investigates incidents, identifies root causes, and executes safe mitigations under human supervision. You will prototype, build, and ship AI systems, influencing strategy and mentoring others while partnering with Infrastructure, AI, Product, and

Qualifications

• Bachelor's degree in Computer Science or related field.
• 12+ years in software engineering, large-scale distributed systems.
• Experience setting technical direction across teams.
• Experience applying AI/ML to production problems.
• Proven transition from concept to production deployment.

Responsabilités

• Define architecture for agentic reliability systems at Meta.
• Design, code, and ship production agentic systems.
• Lead development of AI agent for incident investigation and mitigation.
• Improve agent reasoning, context use, and safe execution.
• Collaborate with Infrastructure, AI, Product, and Reliability teams.

Connaissances

Distributed systems

AI in production

Technical leadership

Incident response

Mentoring engineers

Formation

Bachelor's degree in CS/Engineering

Outils

C++

Java

Python

Rust

Description du poste

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 Aff...

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 at Meta.