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Manager Artificial Intelligence Jobs in Colorado

EchoStar

Security AI Technologist

Littleton, CO · On-site

$127K - $181K/yr

The position resolves risk management challenges by establishing continuous monitoring, robust governance, and adversarial testing frameworks for artificial intelligence systems. Successful execution ...

Deloitte

Lead AI and Data Science Engineer II

Denver, CO

$105K - $139K/yr

... manage multiple initiatives. * Collaborate with stakeholders across Talent, business leadership ... Develop full-stack, web-based data and generative artificial intelligence (GenAI) applications that ...

Eliassen Group

Business Intelligence Analyst

Almont, CO · On-site

$50 - $55/hr

... database management. * Proficiency in writing SQL queries, query optimization, debugging, and ... Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its ...

Deloitte

Finance Strategy Senior Consultant

Denver, CO

$119K/yr

Evaluate finance technology solutions, including enterprise resource planning, enterprise performance management, cloud platforms, and artificial intelligence-enabled tools. * Analyze finance ...

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All JobsArtificial Intelligence JobsManager Artificial Intelligence JobsManager Artificial Intelligence Jobs in Colorado

Manager Artificial Intelligence information

See Colorado salary details

$27.3K

$127.9K

$187.8K

How much do manager artificial intelligence jobs pay per year?

As of Aug 10, 2026, the average yearly pay for manager artificial intelligence in Colorado is $127,861.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,780.00 and $165,675.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a manager of artificial intelligence?

To thrive as a Manager of Artificial Intelligence, you need a strong background in computer science, machine learning, and data analytics, often supported by advanced degrees and experience in AI project leadership. Familiarity with AI frameworks such as TensorFlow or PyTorch, experience with cloud platforms, and certifications like AWS Certified Machine Learning are typically valued. Strong leadership, strategic thinking, and effective communication are vital soft skills for guiding teams and aligning projects with business goals. These skills ensure successful development and deployment of AI solutions that drive organizational value and innovation.

How does a manager of artificial intelligence typically collaborate with cross-functional teams within an organization?

A Manager of Artificial Intelligence frequently works alongside data scientists, engineers, product managers, and business stakeholders to align AI initiatives with organizational goals. They facilitate communication between technical and non-technical teams, ensuring that project requirements are clearly understood and that AI solutions support broader business strategies. This collaborative environment often involves regular meetings, progress updates, and joint problem-solving sessions to address challenges and optimize outcomes.

How do you become a Manager Artificial Intelligence?

To become a Manager of Artificial Intelligence, candidates typically need a strong background in computer science, data science, or related fields, along with experience in AI development, machine learning, and leadership. Earning advanced degrees such as a master's or Ph.D. and gaining experience with AI tools and frameworks like TensorFlow or PyTorch are common steps. Leadership skills and knowledge of project management are also important for overseeing AI teams and projects.

What does a manager of artificial intelligence do?

A Manager of Artificial Intelligence oversees teams and projects that develop and implement AI solutions within an organization. Their responsibilities include setting strategic goals for AI initiatives, managing budgets and timelines, coordinating with other departments, and ensuring that AI systems are aligned with business objectives. They also stay updated on the latest advancements in AI technologies and ensure ethical standards and compliance are maintained. This role requires both technical knowledge of AI and strong leadership skills to guide multidisciplinary teams.

What is the difference between Manager Artificial Intelligence vs Data Scientist?

AspectManager Artificial IntelligenceData Scientist
CredentialsMaster's or PhD in AI, Computer Science, or related fieldsMaster's or PhD in Data Science, Statistics, or related fields
Work EnvironmentLeads AI projects, manages teams, collaborates with stakeholdersAnalyzes data, develops models, interprets results
Industry UsageUsed in organizations deploying AI solutions, tech companies, R&DUsed across industries for data analysis, predictive modeling

The main difference is that a Manager Artificial Intelligence oversees AI projects and teams, focusing on strategy and implementation, while a Data Scientist primarily analyzes data and builds models. Managers handle leadership and project management, whereas Data Scientists focus on technical analysis and model development.

What are the most commonly searched types of Artificial Intelligence jobs in Colorado? The most popular types of Artificial Intelligence jobs in Colorado are:
What are popular job titles related to Manager Artificial Intelligence jobs in Colorado? For Manager Artificial Intelligence jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Manager Artificial Intelligence jobs in Colorado look for? The top searched job categories for Manager Artificial Intelligence jobs in Colorado are:
What cities in Colorado are hiring for Manager Artificial Intelligence jobs? Cities in Colorado with the most Manager Artificial Intelligence job openings:
Manager Artificial Intelligence jobs near you
Infographic showing various Manager Artificial Intelligence job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 13% Part Time, and 1% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $127,861 per year, or $61.5 per hour.

Artificial Intelligence ("AI") Architect

STI

Denver, CO • On-site, Remote

Full-time

Re-posted 4 days ago

Job description

Description:
The AI Program Manager will be a key member of the Chief Data Office team, responsible for driving the strategy and execution of an AI framework within the state government. This role will require a unique blend of technical expertise, strategic vision, and leadership skills, including a close collaboration with OIT resources and agency stakeholders across various state departments to develop product roadmaps, govern AI use cases and ensure alignment with the broader state strategy serving Colorado residents. This role will lead the development and implementation of a comprehensive AI framework for the State, ensuring responsible and beneficial use of AI across government agencies.
Responsibilities:
The Chief Data Office (CDO) is seeking a skilled and motivated AI Lead role to spearhead the State of Colorado's efforts in adopting and implementing artificial intelligence across government agencies. This role requires a unique blend of technical expertise, collaborative leadership and ability to drive program details. The AI Lead will be responsible for guiding the development and execution of AI initiatives, ensuring responsible use, fostering innovation, and maximizing the benefits of AI for Colorado residents.
AI Strategy and Implementation
  • Define and champion the vision, strategy and roadmap for AI adoption across state government, aligning with key priorities for Colorado residents
  • Collaborate with agency stakeholders and OIT resources to identify and prioritize AI opportunities that improve efficiency, service delivery, and citizen engagement.

AI Product and Technology Leadership
  • Collaborate with agency stakeholders and product managers to guide the development and deployment of AI solutions.
  • Provide expert advice and support to agencies on AI-related matters, including technology selection, data governance, and responsible AI practices.
  • Stay abreast of advancements in AI technologies, including GenAI, and provide guidance on their responsible application within government.

AI Governance and Compliance
  • Establish and enforce clear processes for AI project assessment, approval, testing, and monitoring to ensure alignment with state objectives and responsible AI principles.
  • Ensure compliance with relevant state and federal laws, regulations, and policies related to AI development and deployment.
  • Contribute to the development and refinement of AI-related policies and regulations to address emerging challenges and opportunities.
  • Proactively identify and mitigate potential biases and risks associated with AI systems to ensure fairness, equity, and accountability.
  • This role requires meticulous attention to detail in all aspects of AI implementation, governance processes, and product support.

GenAI Expertise:
  • Stay abreast of advancements in GenAI applications and techniques.
  • Understand the cost, data constraints, and potential biases associated with GenAI development and their influence on AI product development.
  • Assist engineers in evaluating GenAI solutions and vendors to ensure they meet the state's requirements for ethical AI and responsible use.

Stakeholder Engagement and Communication:
  • Build and maintain strong relationships with key stakeholders including agency leaders, service owners, technology experts, legal counsel, 3rd party vendors, and community representatives.
  • Facilitate cross-agency collaboration and knowledge sharing on AI initiatives.
  • Raise awareness of AI's potential benefits and risks within the state government.
  • Support training and education on AI products and responsible AI practices.

Champion Responsible AI:
  • Champion responsible AI development and deployment practices across state agencies.
  • Promote transparency and accountability in AI product development and deployment.
  • Reinforce human oversight of AI initiatives to maintain ethical and responsible use.

Attention to Detail:
  • This role requires meticulous attention to detail in all aspects of AI implementation, governance processes, and product support.
  • The AI Lead must be able to identify and address potential risks and inconsistencies in AI systems, data, and documentation to ensure accuracy, compliance, and ethical considerations are met.

Qualifications:
  • Education and Experience:
    Bachelor's degree in computer science, data science, or a related field.
    • 5+ years of experience in the field of artificial intelligence, including experience with machine learning, deep learning, natural language processing, and computer vision.
    • 5+ years of experience in a leadership role, with proven ability to develop and implement strategic initiatives.
    • Demonstrated experience in defining product vision, strategy, and roadmaps.
    • Experience in working with cross-functional teams, including engineers, data scientists, and business stakeholders.
    • Experience in product/program management, with a focus on technology or AI-driven products.
    • Experience working in the public sector or with government agencies is highly desirable.

  • Skills and Knowledge:
    • Deep understanding of AI use cases, technologies, ethical considerations, and policy implications.
    • Strong strategic & critical thinking and planning skills.
    • Attention to detail.
    • Strong technical and business communication skills, with the ability to translate complex technical concepts to non-technical audiences.
    • Excellent communication, interpersonal, and presentation skills.
    • Ability to build consensus and collaborate effectively with diverse stakeholders.
    • Knowledge of data governance, security, and privacy best practices.
    • Familiarity with relevant state and federal laws and regulations.
    • Understanding of responsible AI development principles, including fairness, transparency, and accountability.
    • Awareness of cost, and data constraints for GenAI development and their influence on AI product development.
    • Grant proposal development.

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