Director, AI Operations – LLMOps, AgentOps, MLOps

Navy Federal Credit Union

. Lead enterprise LLMOps, AgentOps, and MLOps capabilities across the AI lifecycle, including deployment, evaluation, monitoring, operational governance, and continuous improvement .

Posted 10/14/2026full-timeVienna • Virginia • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading AI lifecycle management, including LLMOps, MLOps, and operational governance, while establishing frameworks for AI observability and reliability. Proven ability to manage multidisciplinary teams and drive strategic technology initiatives in enterprise environments.

Highest-signal resume keywords

AI Lifecycle ManagementOperational GovernanceAI ObservabilityLeadership in AI/ML OperationsAI FinOps

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringPlatform EngineeringAI/ML OperationsDevOpsSite Reliability EngineeringOperational FrameworksIncident ManagementModel Risk ManagementGenerative AICloud-Native Architectures

Soft Skills

Strong Communication SkillsInfluencing Senior Stakeholders

Tools & Technologies

Microsoft AI TechnologiesAzure AI FoundryDatabricksMLflowLangChainLangGraphLangSmith

Certifications & Qualifications

Cloud CertificationsAI CertificationsMachine Learning Certifications

Industry Keywords

Financial ServicesComplianceRisk ManagementOperational ExcellenceHighly Regulated Industries

Tech Stack

Tools & technologies

AzureCloud

About the role

Key responsibilities & impact

Lead enterprise LLMOps, AgentOps, and MLOps capabilities across the AI lifecycle, including deployment, evaluation, monitoring, operational governance, and continuous improvement
Establish enterprise operational standards, controls, and operating models for managing AI solutions in production
Own the roadmap, service model, engineering standards, and adoption strategy for shared AI operational capabilities
Define and implement AI observability, reliability, production-readiness, and operational support frameworks
Partner with control functions to operationalize AI evaluation, governance, and risk-management requirements
Lead AI FinOps capabilities, including cost attribution, consumption monitoring, optimization, and capacity planning
Partner with Security, Risk, Audit, Compliance, Architecture, and Infrastructure teams to translate policies and regulatory requirements into operational controls
Develop executive reporting and performance metrics for AI adoption, reliability, utilization, operational risk, cost efficiency, and production health
Evaluate emerging technologies and industry trends to improve enterprise AI operational maturity and scalability
Build and lead a multidisciplinary team, manage strategic technology partners, and drive adoption across AI engineering and delivery organizations

Requirements

What you’ll need

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, DevOps, Site Reliability Engineering, or related disciplines
6+ years of leadership experience managing or 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 and ability to translate complex technical concepts into business outcomes and executive recommendations
U.S. work authorization without current or future sponsorship
Monday–Friday availability, 8:00 AM–4:30 PM
Desired: Experience with Microsoft AI technologies, Azure AI Foundry, Copilot Studio, Databricks, MLflow, LangChain, LangGraph, LangSmith, or similar platforms
Desired: Experience with generative AI, RAG architectures, vector search, orchestration frameworks, and agentic AI solutions
Desired: Experience supporting highly available, member-facing, or mission-critical AI applications
Desired: Familiarity with cloud-native architectures, automation, CI/CD, infrastructure-as-code, and modern engineering practices
Desired: Experience implementing AI governance, model risk management, AI evaluation, FinOps, or responsible AI controls
Desired: Experience within financial services, credit unions, or other highly regulated industries
Desired: Advanced degree and/or relevant cloud, AI, or machine learning certifications

Benefits

Comp & perks

Highly competitive pay
Generous benefits and perks
Meaningful career experience
Energized, engaged, and committed culture
Appreciation and recognition for teams
Employee accommodations and assistance during the hiring process, where applicable