Incident Response Manager - Product & Engineering

We are looking for an Incident Response Manager to serve as the operational backbone of how Anthropic handles incidents. When things go wrong, you are the person who makes sure the right people are in the room, the right information is flowing, and nothing falls through the cracks.

The right person for this role brings structure and rigor to high-volume, high-stakes situations without waiting for a playbook to be handed to them. You will work across engineering, product, security, legal, go-to-market, and leadership to ensure Anthropic responds to incidents with speed, clarity, and accountability. This is not a role where you follow existing runbooks; it is a role where you write them, and where you operate effectively even when the runbook does not yet exist., * Build the incident response management function, establishing the processes, tooling, and operational standards that define how we handle incidents at scale

• Serve as an on-call incident commander, driving coordinated response across technical and non-technical stakeholders during incidents of varying severity, including managing multiple active incidents simultaneously
• Engage the right people at the right time, with a strong sense of urgency, bringing order and direction to fast-moving, ambiguous situations
• Own incident communications end-to-end, from real-time internal coordination to external channels like status pages, direct customer outreach, and stakeholder updates, ensuring they reflect Anthropic’s commitments to safety, transparency, and accuracy
• Participate in blameless incident reviews, contributing operational context and helping drive follow-through on critical remediations so the same class of incident does not recur
• Partner with engineering teams to develop and maintain incident response policies, procedures, and escalation frameworks that scale with Anthropic’s growth
• Partner with engineering, product, security, legal, and go-to-market teams to continuously improve how the organization detects, responds to, and learns from incidents

• Have 5+ years of experience in incident management, with direct experience managing technical product or infrastructure incidents (not exclusively security or trust and safety)
• Have built or significantly shaped an incident response program, ideally at a high-growth startup or in an environment where you had to create structure rather than inherit it
• Demonstrate a strong sense of ownership and urgency, with the ability to operate independently and make sound decisions under pressure without waiting for direction
• Are comfortable working in unprecedented situations where processes are still being defined and guidance may be incomplete or conflicting, leaving things better than you found them
• Have a track record of effective cross-functional collaboration, particularly with engineering, security, legal, communications, go-to-market, and executive leadership
• Bring a blameless, learning-oriented mindset to incident reviews, focused on systemic improvement rather than individual fault
• Have experience with cloud infrastructure incidents and enough technical depth across the stack to engage meaningfully with engineering teams during response, including comfort navigating distributed systems, monitoring tools, and logs
• Are analytically minded, with experience using data (incident metrics, queries, trend analysis) to inform decisions during response and to drive operational improvements over time
• Communicate clearly and calmly under pressure, both in real-time coordination and in post-incident written communications
• Thrive in high-volume, fast-paced environments and are energized by bringing operational discipline to complex, evolving situations, Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

For sales roles, the range provided is the role’s On Target Earnings (“OTE”) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $290,000-$365,000 USD, Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates’ AI Usage: Learn about our policy for using AI in our application process.

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems., We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact - advancing our long-term goals of steerable, trustworthy AI - rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We’re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.