Senior Lead Secure AI Engineer – ML & Security

JPMorgan Chase & Co.; Columbus (OH); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. in Columbus, Ohio is seeking a Senior Lead AI Security Engineer to design and deliver secure AI solutions for critical cyber use cases.

You will shape platform standards and governance while collaborating with cross-functional teams to drive secure AI innovation. The role emphasizes building secure LLM/RAG services, integrating with SIEM/XDR, and establishing SDLC guardrails with measurable metrics and post-deployment monitoring.

Qualifications

• 7+ years in software/security engineering with hands-on cyber/ SecOps/ AppSec experience.
• 3+ years building and operating applied ML/LLM systems in production (RAG pipelines, embeddings, vector DBs).
• Proficiency in Python and at least one of Java/Scala/TypeScript; knowledge of microservices, APIs, containers, Kubernetes.

Responsibilities

• Lead end-to-end design and delivery of AI solutions for cyber use cases.
• Build secure LLM/RAG services and ML pipelines integrated with SIEM/XDR, EDR, SOAR, IAM, ITSM, and cloud telemetry.
• Establish engineering standards for secure AI, including prompt security, input/output validation, and secrets handling.
• Create evaluation harnesses with metrics, datasets, adversarial tests, and KPI definitions.
• Partner with platform teams to stand up reusable AI components and governance workflows.
• Implement drift and quality monitoring; define SLAs/SLOs; build incident response runbooks.

Skills

Python

LLM systems

Kubernetes

Security engineering

Software engineering

Tools

LangChain

LlamaIndex

PyTorch

TensorFlow

Kafka

Job description

JPMorgan Chase & Co. in Columbus, Ohio is seeking a Senior Lead AI Security Engineer to design and deliver secure AI solutions for critical cyber use cases.

You will shape platform standards and governance while collaborating with cross-functional teams to drive secure AI innovation. The role emphasizes building secure LLM/RAG services, integrating with SIEM/XDR, and establishing SDLC guardrails with measurable metrics and post-deployment monitoring.