Senior Lead Security Engineer, AI

Columbus, NE - USA

Monthly Salary: Not Disclosed

Posted on: Yesterday

Vacancies: 1 Vacancy

Job Summary

Description

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 23 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 privacy and data protection; ability to partner with governance to meet documentation and monitoring requirements.
Demonstrated ability to ship secure reliable AI features with clear metrics and post-deployment monitoring.

Preferred qualifications capabilities and skills

Experience building developer copilots for AppSec/DevSecOps (IaC scanning secrets detection SAST/DAST triage).
Cloud security engineering across one or more major providers; IaC and policy-as-code.
Experience or exposure to Cyber operations Adversarial ML and LLM red teaming experience (prompt injection data exfiltration model abuse poisoning defenses).
Graph ML for identity/threat detection; anomaly detection over telemetry.
GPU optimization model quantization/distillation and on-prem/private model deployment.
Familiarity with governance for AI/ML systems in regulated environments.

Required Experience:

Senior IC

DescriptionJob SummaryAs 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 ...

Description

Job Summary

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 23 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 privacy and data protection; ability to partner with governance to meet documentation and monitoring requirements.
Demonstrated ability to ship secure reliable AI features with clear metrics and post-deployment monitoring.

Preferred qualifications capabilities and skills

Experience building developer copilots for AppSec/DevSecOps (IaC scanning secrets detection SAST/DAST triage).
Cloud security engineering across one or more major providers; IaC and policy-as-code.
Experience or exposure to Cyber operations Adversarial ML and LLM red teaming experience (prompt injection data exfiltration model abuse poisoning defenses).
Graph ML for identity/threat detection; anomaly detection over telemetry.
GPU optimization model quantization/distillation and on-prem/private model deployment.
Familiarity with governance for AI/ML systems in regulated environments.

Required Experience:

Senior IC

Key Skills

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JPMorganChase

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans ov ... View more

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