Company Description
Anomali is headquartered in Silicon Valley and is the Leading AI-Powered Security Operations Platform that is modernizing security operations. At the center of it is an omnipresent intelligent and multilingual Anomali Copilot that automates important tasks and empowers your team to deliver the requisite risk insights to management and the board in seconds. The Anomali Copilot navigates a proprietary cloud-native security data lake that consolidates legacy attempts at visibility and provides first-in-market speed scale and performance while reducing the cost of security analytics. Anomali combines ETL SIEM XDR SOAR and the largest repository of global intelligence in one efficient platform. Protect and drive your business with better productivity and talent retention.
Do more with less. Be Different. Be the Anomali.
Job Description
Were seeking a Senior Platform Engineer to design build and operate the orchestration layer for agentic AI across our security platform.
In this hands-on engineering role you will own the architecture and implementation of services that coordinate agents and tools to drive research detection and automated response -- reliably safely and at production scale.
Youll operate agentic workflows processing tens of thousands of SOC alerts per minute enabling analysts to automate triage reduce mean time to response (MTTR) and deliver actionable risk insights to management with confidence.
This role provides high technical impact shaping platform architecture engineering standards and operational best practices while collaborating across Product Data Science Security Research and UX teams.
Key Responsibilities
o Orchestrate autonomous workflows: Design and operate the control plane that plans coordinates and monitors agents and their tools including memory management and long-running tasks.
o Build reliable services: Develop and ship production-grade services with clear APIs strong correctness guarantees graceful degradation and async/streaming patterns where appropriate.
o Agentic AI platform engineering: Implement multi-agent orchestration tool-using agents retrieval-augmented workflows prompt orchestration and memory persistence.
o Safety evaluation and guardrails: Implement runtime checks red-teaming and continuous evaluation to balance quality latency and cost; ensure traceability and auditability of agent decisions.
o Observability and operations: Define and monitor SLOs/SLIs instrument tracing metrics and logs; conduct capacity planning incident reviews and post-incident analysis; implement rollback and resilience strategies.
o Cost Latency and throughput optimization: Continuously evaluate and optimize system performance reliability and resource utilization of large-scale AI workloads.
o Collaborate cross-functionality: Partner with Product Data Science GTM and UX teams to translate use cases into composable tools and services.
Qualifications
Required Skills and Experience
o 5 years of building production cloud services at scale.
o Strong proficiency in Python (or similar) and modern API design.
o Hands-on experience shipping agentic AI or tool-using agent systems to production.
o Proven track record of building reliable observable systems with automated testing and continuous delivery.
o Experience operating production services with a security-first mindset.
o Familiarity with distributed systems and real-time processing at high scale (tens of thousands of events per minute).
o Excellent communication skills with the ability to articulate architectural trade-offs clearly to engineers PMs and analysts.
o This position is not eligible for employment visa sponsorship. The successful candidate must not now or in the future require visa sponsorship to work in the US.
Preferred Qualifications
o Experience with retrieval-augmented workflows prompt optimization and evaluation frameworks for AI workloads.
o Hands-on experience with multi-agent systems in production environments.
o Background in security operations or platforms (SIEM XDR SOAR) and familiarity with enterprise security standards.
o Experience working in fast-paced startup or high-growth environments.
o Demonstrate ability to balance reliability cost and latency trade-offs for complex AI services.
o Familiarity with explainability auditability and compliance of autonomous AI workflows.