Director, AI Operations; LLMOps​/AgentOps​/MLOps

Position: Director, AI Operations (LLMOps / AgentOps / MLOps)
Job-:
Data Engineering (AI/ML/NLP)

Location:

Vienna, VA, United States Workplace:
Hybrid

Schedule:

Full time, Regular Hours Posted:
Closes:
Targeted Salary Range:
Negotiable based on experience and qualifications

Navy Federal Credit Union currently does not provide sponsorship for this role. Applicants must be authorized to work in the United States without the need for current or future sponsorship.

The Director, Enterprise AI Operations (LLMOps / Agent Ops / MLOps) leads the enterprise capabilities, platforms, standards, and operating model required to deploy, govern, operate, and continuously optimize AI solutions s leader is responsible for establishing the production frameworks, operational services, engineering practices, and automated governance controls that enable AI delivery teams to move solutions efficiently from experimentation into secure, reliable, and well-governed production environments.

Working closely with Infrastructure, Data, Cybersecurity, Architecture, Risk, and Business teams, the Director will drive adoption of enterprise AI capabilities that accelerate delivery while maintaining operational excellence, regulatory compliance, and responsible AI practices. The role will build and lead a multidisciplinary team, manage strategic vendor relationships, and influence enterprise platform and operating-model decisions that enable trusted AI solutions for members and team members.

Qualifications Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related technical discipline, or the equivalent level of work experience
10+ years of experience in software engineering, platform engineering, AI/ML operations, Dev Ops, Site Reliability Engineering, or related disciplines. 6+ years of leadership experience managing/leading engineering, operations, platform, or AI-focused teams. Experience operationalizing machine learning, generative AI, or agentic AI solutions in large-scale enterprise environments. Strong understanding of AI lifecycle management, including deployment, monitoring, governance, evaluation, continuous improvement, and retirement. Experience establishing operational frameworks, standards, and governance practices for enterprise technology platforms.

Knowledge of AI observability, reliability engineering, incident management, and operational excellence practices. Understanding of AI security, privacy, identity and access management, compliance, model risk, and responsible AI principles. Experience managing large initiatives, vendor relationships, technology investments, budgets, and strategic roadmaps. Proven ability to influence senior stakeholders and drive alignment across technology and business organizations. Strong communication skills with the ability to translate complex technical concepts into business outcomes and executive recommendations.

Desired Qualifications

Experience with Microsoft AI technologies, Azure AI Foundry, Copilot Studio, Databricks, MLflow, Lang Chain, Lang Graph, Lang Smith, or similar platforms.

Experience with generative AI, RAG architectures, vector search, orchestration frameworks, and agentic AI solutions. Experience supporting highly available, member-facing, or mission-critical AI applications. Familiarity with cloud-native architectures, automation, CI/CD, infrastructure-as-code, and modern engineering practices. Experience implementing AI governance, model risk management, AI evaluation, Fin Ops, or responsible AI controls.

Experience with in financial services, credit unions, or other highly regulated industries. Advanced degree and/or relevant cloud, AI, or machine learning certifications. Leadership Competencies Thinks in terms of end-to-end systems and shared accountability, balancing business outcomes, operational excellence, governance, and risk management. Builds scalable, reusable capabilities that accelerate delivery across multiple teams and business functions. Establishes a culture of reliability, automation, accountability, and continuous improvement.

Develops high-performing teams and technical leaders while fostering collaboration across organizational boundaries. Influences enterprise decisions through partnership, expertise, and measurable outcomes. Additional Information

Hours:

Monday - Friday, 8:00AM - 4:30

PM

Location:

820 Follin Lane, Vienna, VA 22180

Responsibilities Lead enterprise LLMOps, Agent Ops, and MLOps capabilities across the AI lifecycle, including deployment, evaluation, monitoring,…