Senior Agentic AI Engineer, Anomali

• 5+ years of building production cloud services at scale
• Strong proficiency in Python (or similar) and modern API design
• Hands-on experience shipping agentic AI or tool-using agent systems to production
• Proven track record of building reliable, observable systems with automated testing and continuous delivery
• Experience operating production services with a security-first mindset
• Familiarity with distributed systems and real-time processing at high scale (tens of thousands of events per minute)
• Excellent communication skills with the ability to articulate architectural trade-offs clearly to engineers, PMs, and analysts
• 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

Desirable

• We're seeking a Senior Agentic AI 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
• You'll 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
• 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
• Build reliable services: Develop and ship production-grade services with clear APIs, strong correctness guarantees, graceful degradation, and async/streaming patterns where appropriate
• Agentic AI platform engineering: Implement multi-agent orchestration, tool-using agents, retrieval-augmented workflows, prompt orchestration, and memory persistence
• 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
• 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
• Cost, Latency, and throughput optimization: Continuously evaluate and optimize system performance, reliability, and resource utilization of large-scale AI workloads
• Collaborate cross-functionality: Partner with Product, Data Science, GTM, and UX teams to translate use cases into composable tools and services