Senior Lead Security Engineer, AI

Job Summary

As a Senior Lead AI Security Engineer in our Cybersecurity team, you will design and deliver secure artificial intelligence solutions that support critical cyber use cases.

You will play a key role in shaping platform standards and governance, collaborating with cross-functional teams, and driving innovation in secure AI.

Together, we will build foundational capabilities and create lasting impact for our organization and the wider community.

Job responsibilities


* Lead end-to-end design and delivery of AI solutions for cyber use cases, from problem framing and data integration to model development, evaluation, deployment, and monitoring.


* Build secure LLM/RAG services and ML pipelines that integrate with SIEM/XDR, EDR, SOAR, IAM, ITSM, CMDB, code repos, and cloud telemetry.


* Establish engineering standards for secure AI: prompt security, tool/function calling patterns, input/output validation, PII masking, secrets handling, and deterministic fallbacks.


* Create evaluation harnesses with offline/online metrics, golden datasets, adversarial prompt sets, jailbreak tests, and safety/quality KPIs.


* Partner with platform teams to stand up reusable AI components: LLM gateways, vector stores, feature stores, evaluation/observability, and governance workflows.


* Implement drift and quality monitoring; define SLAs/SLOs; build incident response runbooks for AI-enabled services.


* Collaborate with risk and MRGR-style governance partners to meet documentation, validation, and attestations; maintain model/AT inventories, monitoring plans, and change logs.


* Deliver measurable impact: reduce MTTR, improve detection precision, automate control evidence collection, and accelerate secure engineering.


* Mentor engineers and analysts; publish playbooks, templates, and safe prompt libraries; lead brown-bags and office hours for adoption.


* Drive a roadmap of 2-3 flagship capabilities per year (e.g., SOC triage assistant, controls automation agent, DevSecOps code copilot).

Required qualifications, capabilities, and skills


* Minimum 7 years of software/security engineering, including hands-on experience in one or more of: detection engineering, SecOps, AppSec/DevSecOps, or cloud security.


* Minimum 3 years building and operating applied ML/LLM systems in production (RAG pipelines, embeddings, fine-tuning/specialization, vector databases, model serving).


* Proficiency in Python and at least one of: Java, Scala, or TypeScript; experience with microservices, APIs, containers, and Kubernetes.


* Familiarity with SIEM, EDR, SOAR, IAM, and ITSM integrations; streaming/data engineering with Kafka or similar.


* Experience with LLM orchestration and guardrails (prompt engineering, injection defense, tool calling, safety filters).


* Hands-on with ML/LLM ecosystems: PyTorch or TensorFlow; scikit-learn; LangChain/LlamaIndex; ONNX/Triton/Ray


* Strong understanding of secure SDLC...