AI & Automation Engineer

Role Summary

The Senior AI Engineer leads technical design and delivery of AI automation across multiple Security Operations Center (SOC) workflows and services. You will remain hands-on while shaping technical approach, resolving ambiguous requirements, and building capabilities other engineers can reuse. You will partner across teams to improve investigation quality and response time and establish engineering standards.

What You Will Do

• Lead complex initiatives spanning diverse security services teams; resolve design tradeoffs and implement critical components using large language models (LLMs), agents, and retrieval pipelines.
• Define reusable architecture for agents, retrieval-augmented generation (RAG), and tool integrations; choose deterministic or model-driven approaches based on evidence, risk, and cost.
• Establish evaluation methods and release criteria across workflows, covering factual accuracy, reliability, false positives, and regressions against validated evidence.
• Design consistent controls for least-privilege access, sensitive data, prompt injection, output validation, and analyst approval of high-impact response actions.
• Lead SIEM, SOAR, XDR/EDR, threat intelligence, and case management integration design; address scale, API failures, and dependencies across services.
• Improve shared Python components, testing, CI/CD, observability, and rollback practices; lead design reviews and coach engineers on difficult implementation decisions.
• Own reliability and measurable outcomes across related workflows, using investigation quality, analyst time saved, success rates, latency, and cost to guide improvements.
• Shape priorities with Security Operations, Threat Research, Data Science, and DevOps; coordinate technical dependencies, resolve production issues, and document architecture and operating standards.

What You Will Bring

Essential

• 7+ years building production software, including 2+ years with LLMs, agents, or applied ML; 1+ year in or alongside a SOC or security team.
• Deep Python and API engineering skills; experience evaluating providers such as OpenAI or Anthropic and open-source models for production use.
• A record of leading architecture and delivery across multiple workflows or services, with reusable designs adopted by other engineers.
• Experience setting AI evaluation and release criteria, diagnosing systemic failure modes, and balancing quality, security, latency, and cost.
• Strong security operations knowledge and experience designing secure integrations, evidence handling, and appropriate analyst oversight for automated response.
• Experience designing and operating distributed or event-driven cloud services, including testing, CI/CD, observability, resilience, and production of incident resolution.
• Ability to turn ambiguous needs into technical plans, influence decisions across teams, and coach senior engineers while remaining hands-on.

Nice to have

• Experience with SQL, Taegis, Sigma detection rules, or mapping detections to MITRE ATT&CK.
• Experience with vector databases, hybrid retrieval, model fine-tuning, or agent orchestration frameworks.
• Background in incident response, network traffic analysis, or Windows event log analysis.
• Experience with containerized or event-driven services, or open-source contributions in security or ML tooling.