Senior AI/ML Engineering Manager — AI-SDLC Innovator

Lockheed Martin Corporation; Texas; On-site; USD 183,000 - 339,000; Full time

Benefits offered by this job

Medical, Dental, Vision

401(k) match

Paid time off

Parental Leave

Education Assistance

Job summary

Lockheed Martin Corporation seeks an Advanced Solutions AI/ML Engineering Senior Manager to define and build the AI-SDLC capability, covering requirements, design, code generation, testing, deployment, and sustainment. The goal is faster, more automated software delivery and reduced total cost of ownership by moving toward in-house AI-enabled tooling.

The leader will manage a multi-team organization of ML, software, and MLOps engineers, set technology direction, ensure security and

Qualifications

• Bachelor’s degree in a STEM field with relevant experience.
• Experience leading managers or technical leads.
• Proven delivery of production AI/ML systems.
• Experience across the full software development lifecycle incl. CI/CD.
• Experience building business cases and budgets.

Responsibilities

• Lead a multi-team org of ML, software, and MLOps engineers; set direction for tech and ensure security and certification.
• Own multi-year vision, budgets, and KPIs; collaborate with Finance, Procurement, Legal, Applications, Cybersecurity, and Program leadership.
• Advise senior leadership on long-range technology investments; drive innovation and adoption across the enterprise.

Skills

LLMs

Agentic AI

Kubernetes

CI/CD

SBOMs

Vulnerability triage

Safety standards

Innovation

Change management

Executive communication

Centers of Excellence

Budgeting

People leadership

AI/ML systems

Education

Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or related STEM field

Tools

LAIC/Genesis

AWS Bedrock

Job description

Lockheed Martin Corporation seeks an Advanced Solutions AI/ML Engineering Senior Manager to define and build the AI-SDLC capability, covering requirements, design, code generation, testing, deployment, and sustainment. The goal is faster, more automated software delivery and reduced total cost of ownership by moving toward in-house AI-enabled tooling.

The leader will manage a multi-team organization of ML, software, and MLOps engineers, set technology direction, ensure security and