Associate Director, AI Application Engineer
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All the relevant skills, qualifications and experience that a successful applicant will need are listed in the following description.
In this role, you lead applied AI initiatives across classified and unclassified environments, delivering practical AI/ML capabilities into programs. You will push secure AI pipelines, guide teams, and help transition research into production. You collaborate across engineering, research, leadership, and customers to ensure compliant, high-value AI solutions. Your work shapes mission-critical capabilities while aligning with RTX’s safety and innovation priorities. This is a hands-on, impact-driven leadership role with a strong focus on real-world deployment.
Compensation / Benefits
- medical, dental, vision
- life insurance
- 401(k) match
- flexible work schedules
- paid time off
- parential leave
Responsibilities
- Integrate and deploy AI/ML models, including LLMs, across environments
- Build and operate secure AI pipelines in cloud, tactical, and embedded settings
- Transition prototypes to production and mature applied research
- Provide organizational enablement through guidance, training, and best practices
- Collaborate with engineering, research, program leadership, and customers
- Evaluate new technologies for security and government standards compliance
- Contribute to proposals and technical communications
- Design and govern agentic AI systems with guardrails and safety measures
- Apply agent-based workflows to improve engineering and mission execution
Key requirements
- STEM degree with at least 12 years of relevant experience
- AI practitioner experience applying AI to SW development, security, automation, and workflows
- Production AI system delivery xhuatnn experience
- Experience designing, training, and deploying LLMs and advanced ML models with secure ML Ops/DevSecOps
- Python proficiency and familiarity with modern ML frameworks
- Experience deploying AI in cloud and embedded environments
- Experience leading workstreams
- Ability to obtain/maintain TS/SCI clearance; U.S. citizenship required
- leadership
- cross-functional collaboration
- technical communication
- LLMs design/train/deploy
- secure ML Ops/DevSecOps
- AI/ML production systems
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