Director, AI Operations (LLMOps / AgentOps / MLOps)
At a glance
Director-level ML Platform & Ops role at Fa Etbx Saasfaprod1. Vienna · full-time · no salary stated · we estimate $192,500–$264,875 across the United States.
Fa Etbx Saasfaprod1 has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Lead production operations for enterprise LLM, agent and machine-learning systems, from deployment and evaluation through monitoring and improvement
- Set the standards and controls for running AI in production, and own the roadmap for shared operational services
- Build observability, reliability, readiness and support practices that protect AI service quality and resilience
- Turn governance and risk requirements into operating controls, while tracking AI costs, usage and capacity
- Lead a multidisciplinary team and technology partners, and report on adoption, reliability, risk, cost and production health
What you bring
- A technical degree or equivalent work experience, plus at least ten years in software, platform, AI/ML operations or a related discipline
- At least six years leading engineering, operations, platform or AI-focused teams
- Experience putting machine-learning, generative AI or agent-based solutions into production at enterprise scale
- A track record creating operating frameworks and governance practices for enterprise technology platforms
Who this fits
This director-level role suits an experienced engineering or operations leader who can guide teams and align technology and business stakeholders. The work is based in Vienna, Virginia, with a Monday-to-Friday schedule from 8:00 a.m. to 4:30 p.m. Applicants must already be authorized to work in the United States without current or future sponsorship.
From the employer
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 / AgentOps / MLOps) leads the enterprise capabilities, platforms, standards, and operating model required to deploy, govern, operate, and continuously optimize AI solutions at scale.
This 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.
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 to ensure service quality and resilience.
Partner with enterprise control functions to operationalize AI evaluation, governance, and risk-management requirements that promote quality, safety, compliance, and responsible AI outcomes.
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 enterprise policies and regulatory requirements into effective operational controls.
Develop executive reporting and performance metrics related to AI adoption, reliability, utilization, operational risk, cost efficiency, and production health, while enabling business owners to measure value realization.
Evaluate emerging technologies and industry trends to improve enterprise AI operational maturity and scalability.
Build and lead a high-performing multidisciplinary team while managing strategic technology partners and driving adoption across AI engineering and delivery organizations.
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/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.
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.
Desired Qualifications
Experience with Microsoft AI technologies, Azure AI Foundry, Copilot Studio, Databricks, MLflow, LangChain, LangGraph, LangSmith, 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, FinOps, or responsible AI controls.
Experience within financial services, credit unions, or other highly regulated industries.
Advanced degree and/or relevant cloud, AI, or machine learning certifications.
Additional Information
Hours:
Monday - Friday, 8:00AM - 4:30PM
Location:
820 Follin Lane, Vienna, VA 22180