Software Engineering Manager, Network Security

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.

The Network Security team's remit is to secure Anthropic's networks across our cloud providers and our bare-metal AI data centers. We own egress and ingress controls, network segmentation, private connectivity between environments, and encryption in transit. We design, build, and maintain these controls, and we write the software that deploys, enforces, and monitors them. These controls protect our model weights, customer data, and internal assets.

We are hiring an Engineering Manager to lead this team. Anthropic is adding data center sites and cloud regions quickly, and the team will grow with that work. In this role you will set the team's charter, practices, and priorities. You will partner with our infrastructure networking, cluster, and data center teams so security is built into network designs from the start. The goal is secure-by-default networking that lets research and product teams use compute in any environment without slowing them down.

Key responsibilities

We're hiring an Engineering Manager to lead a Network Security Engineering team in executing across critical initiatives including, but not limited to:

• Own the network security roadmap: threat model from the management plane through Kubernetes and cloud interconnects, decide what to build, and deliver it
• Be able to reason about the design and implementation of default-deny ingress and egress, segmentation between research, training, and production, private connectivity, and mTLS/service identity across every environment
• Ship these as secure-by-default primitives so new clusters, VPCs, and data center links inherit the right boundaries without security on the critical path
• Join networking, cluster, and data center teams at design time so topology, routing, and firewall decisions carry our invariants from day one
• Build visibility into traffic and boundary drift, with detection for exfiltration paths and automated remediation where safe
• Own the network security evidence for our security goals and compliance: the invariants hold, and you can prove it
• Hire, grow, and retain senior security software engineers; own their career development, and set the practices the team runs on as it scales

• 8+ years of front line management experience
• Low ego, high empathy; has built diverse teams and has former reports who would work for them again
• Experience managing infrastructure or security engineering teams, including hiring, developing, and managing senior and staff engineers
• Has grown engineers into staff or lead roles, and has made the call to move someone out when coaching didn't work
• Kept a team intact and delivering through reorgs, charter changes, or leadership turnover

The annual compensation range for this role is listed below.

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.

• Built or rebuilt a hiring loop and held the bar while adding headcount quickly
• Exposure to large-scale distributed training and what it demands of a network
• Solved end-to-end networking problems directly with internal users, cloud account teams, and hardware or colo vendors
• Has taken infrastructure from zero to one and then to maturity: built the first version where nothing existed, then run and hardened it into a system other teams depend on at production-network reliability

$405,000—$485,000 USD

Logistics

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.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

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.