Software Engineer, AI for Incident Response (Technical Leadership)

Meta; Menlo Park (CA); On-site; USD 219,000 - 301,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Meta is seeking a Software Engineer, AI for Incident Response (Technical Leadership) in Menlo Park to shape the technical direction of an AI-powered incident investigation and mitigation agent. You will design and ship core capabilities, improve root-cause detection, and build evaluative systems that learn from production outcomes, with human oversight and secure, auditable workflows.

The role spans large-scale distributed systems, applied AI, and reliability engineering, collaborating with

Qualifications

• 10+ years of software engineering experience, including experience building and operating large-scale distributed, infrastructure, or production AI systems.
• Experience setting technical direction and leading complex engineering efforts across multiple teams or organizational boundaries.
• Experience applying AI to production problems at scale, including evaluation of system quality and failure modes.
• Recent hands-on experience designing, coding, debugging, and shipping complex production systems.
• Experience building systems that support critical, always-on production workloads.
• Experience diagnosing complex production systems using telemetry, code, configuration, deployments, and dependency information.
• Experience coding in languages such as C++, Java, Python, Rust, or equivalent.
• Experience influencing senior engineers and leaders without direct organizational authority.

Responsibilities

• Define and drive the technical vision, architecture, and execution roadmap for AI-powered incident investigation and mitigation.
• Personally design, code, evaluate, and ship major capabilities in a production agentic system.
• Improve timely root-cause accuracy through better reasoning, skills, tool use, context, memory, planning, and domain knowledge.
• Build the offline evaluation, historical replay, and online experimentation systems needed to measure changes and continuously improve agent behavior.
• Create a transparent, multi-turn experience that supports collaborative investigation with expert responders and agent-led guidance for less frequent responders.
• Enable the agent to reason across telemetry, code, configuration, deployments, service dependencies, operational knowledge, and incident history.
• Build closed-loop learning systems that turn production outcomes and user feedback into evaluations, experiments, and product improvements.
• Advance the system toward progressive autonomy with explicit authorization, validation, auditability, rollback, and human oversight.
• Build an extensible platform that combines shared capabilities with domain-specific skills, tools, and agents contributed by infrastructure and product teams.
• Partner closely with on-call engineers, reliability experts, product groups, data science, and product management to drive accuracy, adoption, and realized operational impact.
• Ensure the system meets a high bar for reliability, latency, scale, security, privacy, and cost.
• Influence technical strategy across organizations and mentor senior engineers working across distributed systems and applied AI

Skills

Technical leadership

Production AI

Distributed systems

Production debugging

C++/Java/Python/Rust

Incident response

Telemetry & Deployments

Stakeholder influence

Job description

As AI agents increasingly write and operate infrastructure, reliability systems must be able to reason and act at machine speed. In this role, you will set the technical direction and drive execution for an AI agent that autonomously gathers context, investigates incidents, identifies likely root causes, builds a safe mitigation plan, and executes it - with humans supervising and able to intervene at any point.The immediate challenge is building an agent that is both highly accurate and broadly trusted. Experienced incident responders need a transparent collaborator that helps them investigate, continuously surfaces relevant evidence, and keeps them in control. Engineers who encounter incidents only occasionally need an agent that leads the investigation and guides them to a safe outcome.You will lead two tightly connected areas: - Agent quality - skills, tools, context, memory, offline evaluation, backtesting, online experimentation, and learning from production outcomes. - Responder experience - a multi-turn interface that gives responders visibility into the agent's work and brings together the operational data they need to make decisions.This is a deeply hands-on technical leadership role at the intersection of large-scale distributed systems, incident response, applied AI, and product engineering. You will personally design and ship critical parts of the system while leading senior engineers across team and organizational boundaries. The long-term opportunity is to help create self-healing infrastructure that resolves production incidents safely at Meta scale.Software Engineer, AI for Incident Response (Technical Leadership) Responsibilities:Define and drive the technical vision, architecture, and execution roadmap for AI-powered incident investigation and mitigationPersonally design, code, evaluate, and ship major capabilities in a production agentic systemImprove timely root-cause accuracy through better reasoning, skills, tool use, context, memory, planning, and domain knowledgeBuild the offline evaluation, historical replay, and online experimentation systems needed to measure changes and continuously improve agent behaviorCreate a transparent, multi-turn experience that supports collaborative investigation with expert responders and agent-led guidance for less frequent respondersEnable the agent to reason across telemetry, code, configuration, deployments, service dependencies, operational knowledge, and incident historyBuild closed-loop learning systems that turn production outcomes and user feedback into evaluations, experiments, and product improvementsAdvance the system toward progressive autonomy with explicit authorization, validation, auditability, rollback, and human oversightBuild an extensible platform that combines shared capabilities with domain-specific skills, tools, and agents contributed by infrastructure and product teamsPartner closely with on-call engineers, reliability experts, product groups, data science, and product management to drive accuracy, adoption, and realized operational impactEnsure the system meets a high bar for reliability, latency, scale, security, privacy, and costInfluence technical strategy across organizations and mentor senior engineers working across distributed systems and applied AIMinimum Qualifications:10+ years of software engineering experience, including experience building and operating large-scale distributed, infrastructure, or production AI systemsExperience setting technical direction and leading complex engineering efforts across multiple teams or organizational boundariesExperience applying AI to production problems at scale, including evaluation of system quality and failure modesRecent hands-on experience designing, coding, debugging, and shipping complex production systemsExperience building systems that support critical, always-on production workloadsExperience diagnosing complex production systems using telemetry, code, configuration, deployments, and dependency informationExperience coding in languages such as C++, Java, Python, Rust, or equivalentExperience influencing senior engineers and leaders without direct organizational authorityPreferred Qualifications:Experience improving agent quality through context engineering, skills, memory, evaluation, automated experimentation, hill climbing, fine-tuning, or reinforcement learningDemonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)Experience building multi-turn, human-agent experiences for complex or high-stakes workflowsExperience building production AI agents that use tools and reason across telemetry, code, configuration, deployments, and operational knowledgeTrack record of taking an ambitious technical product from early adoption to trusted, broad production useExperience designing autonomous or semi-autonomous production actions with identity, authorization, independent validation, auditability, rollback, and escalationExperience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)Experience with incident management, SRE, observability, on-call operations, or automated remediation at significant scaleDemonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologiesExperience building extensible platforms that allow domain teams to contribute specialized capabilities while preserving a coherent user experienceAbout 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 Affirmative 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].$219,000/year to $301,000/year + bonus + equity + benefitsIndividual 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.