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Program Manager Artificial Intelligence Jobs in Washington

SAIC

Artificial Intelligence (AI) SETA

Chantilly, VA

$200K - $240K/yr

As part of the AI research team, the SETA will be trusted to coordinate and manage activities ... Expertise on Artificial Intelligence and high-performance computing topics * Proficiency with ...

SAIC

Artificial Intelligence (AI) SETA

Chantilly, VA · On-site

$200K - $240K/yr

As part of the AI research team, the SETA will be trusted to coordinate and manage activities ... Expertise on Artificial Intelligence and high-performance computing topics * Proficiency with ...

OpenDataJobs

Data Program Manager Role

Washington, DC · On-site

The work Data Program Managers turn a collection of technical projects into one coordinated program ... Technical fluency in data, analytics, software, cloud, or artificial intelligence sufficient to ...

OpenDataJobs

Data Program Manager Role

Washington, DC · On-site

... artificial intelligence initiatives where no single workstream can succeed alone. The work is both ... Data Program Managers establish the operating rhythm, maintain an integrated view of scope and ...

Nationwide IT Services, Inc

Program Manager

Andrews, MD · On-site

$181K - $263K/yr

... Artificial Intelligence Office (CDAO) Support Services for a potential opportunity. The Program Manager is responsible for workforce continuity, performance management, customer coordination ...

New

Nationwide IT Services

Program Manager

MD · On-site

... Artificial Intelligence Office (CDAO) Support Services for a potential opportunity. The Program Manager is responsible for workforce continuity, performance management, customer coordination ...

New

SAIC

Program Manager

Mclean, VA · Hybrid

$200K - $240K/yr

Program Management Subcategory: Program Mgmt Schedule: Part-Time Shift: Day Job Travel: No Minimum ... Artificial Intelligence/Machine Learning, Cyber Security, Cloud Computing and Data management.

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Program Manager Artificial Intelligence information

See Washington salary details

$43.6K

$121.7K

$177.8K

How much do program manager artificial intelligence jobs pay per year?

As of Aug 22, 2026, the average yearly pay for program manager artificial intelligence in Washington is $121,709.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $150,100.00 per year, depending on experience, location, and employer.

What is a program manager artificial intelligence?

Program Managers in Artificial Intelligence (AI) are professionals who oversee and coordinate AI projects and initiatives within an organization. They work closely with cross-functional teams, including data scientists, engineers, and business stakeholders, to ensure that AI programs are delivered on time, within budget, and meet strategic goals. Their responsibilities typically include project planning, resource allocation, risk management, and communicating progress to leadership. Program Managers in AI also help bridge the gap between technical teams and business objectives, ensuring that AI solutions align with organizational priorities.

How does a program manager artificial intelligence typically collaborate with data scientists and engineers on complex projects?

A Program Manager in AI acts as a crucial bridge between stakeholders, data scientists, and engineers to ensure projects align with business goals and technical feasibility. They coordinate regular meetings, facilitate clear communication of requirements, and help resolve blockers that arise during development. By translating business objectives into actionable tasks, they enable cross-functional teams to stay aligned and deliver results efficiently. Additionally, they often oversee timelines, resource allocation, and risk management to keep AI initiatives on track.

What are the key skills and qualifications needed to thrive as a program manager artificial intelligence, and why are they important?

To thrive as a Program Manager in Artificial Intelligence, you need a strong understanding of AI concepts, project management methodologies, and experience overseeing technical teams, often supported by a degree in computer science or engineering and certifications like PMP. Familiarity with AI development tools, cloud platforms (such as AWS, Azure, or Google Cloud), and agile project management systems is typically required. Exceptional communication, stakeholder management, and problem-solving skills help you align cross-functional teams and drive projects to successful completion. These skills and qualities are crucial for delivering complex AI initiatives on time, within budget, and in alignment with organizational objectives.

What are popular job titles related to Program Manager Artificial Intelligence jobs in Washington?

For Program Manager Artificial Intelligence jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Program Manager Artificial Intelligence jobs in Washington look for?

The top searched job categories for Program Manager Artificial Intelligence jobs in Washington are:

Program Manager Artificial Intelligence jobs near you
Infographic showing various Program Manager Artificial Intelligence job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 14% Part Time, 2% Temporary, and 8% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $121,709 per year, or $58.5 per hour.

Artificial Intelligence Technical Lead

Joint Technology Solution, Inc

Silver Spring, MD • On-site, Remote

Full-time

Re-posted 20 days ago

Job description

We are seeking an experienced Subject Matter Expert in Artificial Intelligence. This person shall provide technical Artificial Intelligence (AI) expertise and support services required to advance NWS priorities in science, research, policy, program management, and strategic implementation.
They will serve as the technical lead for AI initiatives, overseeing solution architecture, project delivery, AI/ML development, DevSecOps/MLOps practices, and stakeholder collaboration to advance enterprise AI capabilities.
This support shall include, but is not limited to, the following tasks:
Duties:
User Needs and Technical Project Management Support
  • Translates complex operational, scientific, and business challenges and user feedback into actionable technical requirements, system architectures, and implementation plans for AI-driven solutions.
  • Oversees the lifecycle of AI initiatives from a technical perspective by prioritizing features that maximize organizational value while managing resource constraints and risks.
  • Coordinates between cross-functional teams to ensure that project milestones and AI solutions align with enterprise architecture and cybersecurity requirements as well as meet both technical benchmarks and user expectations.

Technical Consultation and Architecture
  • Provides expert guidance to development teams on AI/ML architectural design, software engineering practices, data pipelines, model selection, deployment strategies, and the implementation of best practices, including testing and maintenance.
  • Conducts rigorous technical assessments and architecture reviews of proposed and ongoing AI projects to assess feasibility, scalability, security, performance standards, operational readiness, and risk.
  • Identifies potential technical bottlenecks and ethical considerations in AI workflows and recommends proactive solutions to timely and responsible delivery.
  • Recommend and implement best practices for software engineering, Development, Security, and Operations (DevSecOps), Machine Learning Operations (MLOps), testing, monitoring, observability, and lifecycle management of AI systems.

Technical Development
  • Leads the end-to-end development of AI projects for NWS enterprise priorities that do not have a development team, ensuring they are built for production-grade reliability and scalability.
  • Implement and support Continuous Integration and Continuous Deployment (CI/CD), DevSecOps, and MLOps practices, including automated testing, model versioning, deployment automation, monitoring, and incident response.
  • Troubleshoot operational issues, performance bottlenecks, and deployment challenges associated with AI systems and supporting infrastructure.
  • Supports the development of proof-of-concepts to test emerging AI technologies and their potential application within the enterprise.

Communications
  • Distills sophisticated AI architectures, concepts, engineering challenges, and model performance metrics into clear, non-technical insights for executive leadership and stakeholders.
  • Prepare technical documentation, implementation plans, architecture diagrams, deployment guidance, and operational support materials.
  • Facilitates dialogue between developers, data scientists, engineers, and product owners to maintain clarity on project goals and ensure continuous feedback.
  • Supports the communication of current NWS AI capabilities as well as future AI opportunities, presenting technical progress, operational risks, strategic wins, and possibilities in formal reports and briefings.
  • Recommend explicitly referencing Development, Security, and Operations (DevSecOps) and Machine Learning Operations (MLOps) practices. These terms communicate that the role is expected to support the operationalization of AI capabilities, including automated deployment pipelines, model versioning, security controls, monitoring, observability, and ongoing maintenance.

Experience:
  • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Information Technology, or related field.
  • Minimum 7-10 years of experience in software engineering, systems architecture, data science, or related technical fields.
  • Minimum 5 years of experience designing, developing, and implementing AI/ML solutions in production environments.
  • Experience leading complex technical projects involving cross-functional teams and stakeholders.
  • Ability to obtain and maintain a Public Trust or other required federal security clearance.
  • Demonstrated experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar technologies.
  • Experience developing and deploying machine learning models in cloud environments such as AWS, Azure, or Google Cloud.
  • Strong knowledge of DevSecOps, MLOps, CI/CD pipelines, and software development lifecycle best practices.
  • Experience designing scalable system architectures and data pipelines.
  • Proficiency in Python and other relevant programming languages.
  • Experience implementing monitoring, testing, version control, and operational support for AI systems.

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