Manager, Corporate Network Engineering

The Corporate Network Engineering team owns Anthropic’s corporate network: the wired, wireless, and edge infrastructure in our offices and research facilities around the world, and the standards, management systems, and telemetry that let a small team run them. We hold that network to the bar of a production service - designed for failure, managed as code, observable end-to-end, and secure by default - while delivering reliable connectivity to the people who depend on it every day.

You’ll set the technical direction together with your engineers and own the final decision on it and on the architecture standards, review and guide designs and the hard trade-offs, and lead vendor and platform decisions. You’ll lead and grow a small team of network engineers: set priorities, drive decisions to closure, hire, and develop people. The team is small and the scope is broad, so this role needs real depth in campus and edge networking, judgment about what to standardize, automate, buy, and build, and the range to go from a wiring-closet decision to a budget defense in the same afternoon.

You’ll report to the head of IT Engineering and partner closely with our Buildouts, AV, and Endpoint teams; with Security Engineering on network security, authentication, and detections; with Physical Security, whose systems are critical for protecting Anthropic employees and depend on a reliable network; with Workplace, Real Estate, Procurement, and external logistics and integration partners on new site buildouts; and with our production networking teams, whose bar for reliability and automation is the one we hold ourselves to. Your work will directly shape how we scale to AI Safety Level 4 and beyond.

Responsibilities

• Lead and grow the Corporate Network Engineering team - hiring, development, performance, planning, and prioritization
• Set technical direction with the team and own the final call on architecture standards across edge, campus switching, wireless, segmentation, out-of-band management, and telemetry; review designs and risky changes, and step in on the hard problems
• Own reliability and operations: monitoring people act on, incident response and post-incident reviews that produce changes, an on-call and escalation model a small team can sustain, change safety, and lifecycle currency
• Move the fleet toward network-as-code: templated configuration with change control, staged rollouts, drift detection, and automation that removes operational toil
• Partner with Security Engineering and Detection & Response on network authentication, segmentation, and the network as a detection source
• Deliver networks for new offices and research facilities and upgrade existing sites through live migrations - with Buildouts, AV, Physical Security, Workplace, Real Estate, and our logistics partners - while keeping interruptions to employees minimal
• Own vendor, carrier, and integrator relationships and the network hardware budget: evaluations, contracts, lead times, and multi-year refresh, * Have led corporate networking at a company that added offices faster than it added network engineers
• Have implemented certificate-based network authentication (802.1X/EAP-TLS or equivalent) and identity- or device-based segmentation at scale
• Have shipped network configuration as code and built telemetry pipelines that security and support teams actually use
• Have designed dense wireless for large event spaces and high-occupancy floors
• Have been through multiple office builds with real estate and construction teams - including networks that physical security systems depend on - and know what to ask for before the walls close
• Have managed integrators, MSPs, or smart-hands providers as an extension of a small team while keeping design authority in-house

Technical Skills

We’re looking for deep, hands-on experience in each of these - not surface familiarity:

• Enterprise edge: firewalls and routing (HA design, routing protocols, policy management across a fleet)
• Campus switching and high-density enterprise wireless (L2/L3 design, redundancy, RF design, 6 GHz, high-density venues)
• Segmentation and access control (certificate-based 802.1X, dynamic segmentation, guest and IoT isolation)
• Out-of-band management and secure, auditable administrative access
• Network automation and configuration as code (Python, templating, vendor APIs, source control, CI)
• Network observability (streaming telemetry, flow and log pipelines)
• Physical infrastructure for buildouts (MDF/IDF design, structured cabling, power and cooling, carrier and path diversity)

• Have 10+ years designing, building, and operating enterprise campus and edge networks, including at least one environment with dozens of sites across regions
• Have 5+ years leading engineers, including at least 3 years as a people manager
• Lead through technical judgment: whether or not you’ve been hands-on-keyboard lately, you can go from architecture to protocol behavior to failure modes with your engineers, and your reviews make their designs better
• Default to the secure design, then do the creative work to make it painless for the people using it - and can walk an executive or an engineer through the trade-off and make a recommendation
• Have run the operational side, not just designed it: out-of-band access, monitoring people act on, an on-call model a small team can sustain, and change safety
• Are pragmatic about what to build, buy, or automate, have run vendor evaluations with real money at stake, and chase problems across organizational boundaries to the actual root cause
• Communicate clearly with engineers, executives, contractors, and landlords, and can bring a room of senior engineers with strong opinions to a decision they’ll commit to
• Want real technical ownership with a small team - including if you’ve led a larger organization before - and care about building infrastructure for an organization trying to get AI right, 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: $285,000-$325,000 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.