软件工程师，事件响应AI

Meta（Meta Platforms）岗位：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 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

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

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 diagnosing complex production systems using telemetry, code, configuration, deployments, and dependency information

Experience translating customer needs into technical architecture and driving adoption of a platform or developer product

Experience influencing senior engineers and leaders without direct organizational authority

Experience improving agent quality through context engineering, skills, memory, evaluation, automated experimentation, hill climbing, fine-tuning, or reinforcement learning

Demonstrated 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 workflows

Experience building production AI agents that use tools and reason across telemetry, code, configuration, deployments, and operational knowledge

Track record of taking an ambitious technical product from early adoption to trusted, broad production use

Experience designing autonomous or semi-autonomous production actions with identity, authorization, independent validation, auditability, rollback, and escalation

Experience 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 scale

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Experience building extensible platforms that allow domain teams to contribute specialized capabilities while preserving a coherent user experience

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.

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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.

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Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

10+ years of software engineering experience, including experience building and operating large-scale distributed, infrastructure, or production AI systems.