Staff / Senior Software Engineer, Security Fusion Platform
San Francisco, CA | New York City, NY | Seattle, WA · San Francisco · USD 320,000-405,000 / year · Hybrid · Posted Sep 29, 2026
At a glance
- Workplace
- Hybrid
- Location
- San Francisco, CA | New York City, NY | Seattle, WA · San Francisco
- Salary
- USD 320,000-405,000 / year · Base salary
- Visa sponsorship
- Visa sponsorship available
About Anthropic
- 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.
About the role
- Data Center Security Engineering (DCSE) owns physical security across Anthropic's data center footprint, and the Security Fusion Platform is where physical security signals from across that footprint are correlated.
- This is a foundational role where you will build the software platform that carries a signal from source to analyst decision, ship its first versions, and keep them running in production.
- You'll work alongside engineers focused on the sites themselves, and what you lead, you own end to end from design to production.
Responsibilities
- Design and build the event bus and normalized event schema: source identity, sequencing, health state, and the adapter contract that owners of each sensor and system feed build to, plus adapters where needed
- Build correlation and alerting: the rules and services that turn events from independent sources into alerts an analyst can act on
- Build the classification and analytics pipelines: computer vision and multi-sensor fusion, with results landing on the event bus
- Build analyst surfaces: the queue, escalation tooling, dashboards, camera viewers, and video wall content a 24/7 watch works from, plus video analytics integration so camera streams arrive on the bus as events
- Deliver audit evidence: durable, tamper-evident event history, evidence exports, and the retention and access controls around them
- Instrument metrics and self-monitoring: detection rates, nuisance ratios, alert aging, time to resolve; heartbeats and loss-of-telemetry alarms on every feed, tested fail-secure behavior, and change audit on every rule
- Deploy across sites: site-local components, central services, and the sync that keeps configuration, rules, and state consistent, then commission each site and hand over to the analysts
- Specify the compute the platform runs on (servers, storage, and the platform's network segment) to the team's segmentation and hardening baseline
- Write requirements and acceptance criteria for what vendors and integrators deliver, review deliverables against them, and make the call on accepting or rejecting the work
Requirements
- Have built and run event-driven backend systems in production
- Are proficient in at least one backend language such as Python, Go, or Rust, and have worked with a message bus or event streaming system such as Kafka
- Have owned a system end to end: set the design, made the tradeoffs, shipped it, and answered for it in production
- Have integrated with external systems you did not control (vendor APIs, on-prem appliances, video platforms, building systems) and designed for a life beyond any one vendor
- Have directed vendor or integrator work: written requirements and acceptance criteria, reviewed deliverables against them, and decided what gets accepted
- Design for the failure you won't see coming (a silent feed, a lost network path, a replayed event, a de-tuned rule), know how your system behaves when a source lies or goes quiet, and test for it
- Build tools for people who use them under pressure and iterate with those operators
- 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
Preferred qualifications
- Experience building or operating a security operations platform (SOC, physical security operations, or the detection engineering behind one)
- Experience building ML or computer vision inference pipelines over video and sensor streams
- PSIM (physical security information management) or VMS (video management system) integration experience, or familiarity with physical access control and building systems data
- Experience producing evidence for auditors or assessors: log integrity, retention, chain of custody
- Experience using AI-assisted development tooling as a core part of your workflow
Benefits
- Optional equity donation matching
- Generous vacation
- Parental leave
- Flexible working hours
Workplace
- Involves regular travel to data center sites
- Location-based hybrid policy requiring staff to be in one of the offices at least 25% of the time
Skills
- Python
- Go
- Rust
- Kafka
- Computer Vision
