As a Senior Machine Learning Engineer - Agentic AI within Data Impact & Governance, you will be at the forefront of designing and operating the platform capabilities that enable autonomous and semi-autonomous AI systems to function reliably across clinical, research, and operational domains.

Company: The University of Texas MD Anderson Cancer Center

Role: Senior Machine Learning Engineer - Agentic AI

Location: Houston, TX (Remote within Texas only)

Experience:

5 years of experience in machine learning engineering, data science, data engineering, and/or software engineering
3+ years as a Senior ML Engineer focused on agentic AI systems

Key Skills:

Python
PyTorch
LangGraph
LangChain
AutoGen
CrewAI
Semantic Kernel
Airflow
Prefect
Temporal
Ray
Kubernetes

Qualification:

Bachelor's degree in Computer Science, Software Engineering, Data Science, Physics, Math & Statistics, or another related engineering discipline
Master's degree or PHD with a concentration in Science, engineering, or related field (Preferred)

Role Focus:

Lead the design, evolution, and operation of the enterprise agentic AI platform
Build platform components that enable interoperability between first-party and third-party agents
Define and document standardized integration patterns connecting agents with enterprise business systems
Provide reusable platform services, reference implementations, and SDKs
Design and operate validation and de-risking frameworks
Establish and enforce platform standards for agent development
Participate in platform governance, release coordination, and incident response

Additional responsibilities:

Implement platform safeguards such as fallback mechanisms, rollback strategies, approval gates, rate limiting, audit trails, and kill-switch capabilities
Partner with software engineering, security, IT, and health IT stakeholders to deploy agentic AI capabilities in secure enterprise environments
Support responsible AI practices through traceability of prompts, policies, tools, models, agent actions, and documentation of known failure modes and limitations

Nice to have:

Experience designing, deploying, and maintaining agentic AI systems that operate autonomously and collaboratively across distributed environments
Experience in monitoring and troubleshooting autonomous agents post-deployment
Experience raising the technical bar for team members
Experience technically evaluating third-party agentic AI platforms within clinical workflows

Other:

Outstanding Benefits: paid medical benefits, generous paid time off (PTO), and strong retirement plans
Enterprise-Level Impact: Architect platform capabilities that support AI agents operating across complex health IT systems and enterprise workflows
Technical Leadership: Shape standards, integration patterns, and guardrails governing agentic AI at organizational scale
Career Growth & Visibility: Partner closely with enterprise architects, applied MLEs, data scientists, IT, and governance leaders on high-impact AI initiatives
Responsible AI Innovation: Work in a mission-driven institution where responsible AI, safety, and trust are central to technology strategy
Collaborative Culture: Join a highly skilled team that values intellectual rigor, mentorship, and cross-disciplinary collaboration
Minimum Salary: $146,500, Midpoint Salary: $183,000, Maximum Salary: $219,500

Senior Machine Learning Engineer

Skills Required

Description