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Senior Generative Ai Engineer Jobs in Colorado (NOW HIRING)

Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks. * Proficiency in at least one programming language such as Python ...

AI Engineer

Denver, CO · On-site

$110K - $150K/yr

Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks. * Proficiency in at least one programming language such as Python ...

Senior AI Automation Engineer (Gen AI Developer) Location: Denver, CO Duration: 6-12+ months Role ... Generative AI and enterprise agent-based solutions| focusing on the design| development| and ...

Job Summary : eTeam is a company looking for a Generative AI Developer. The role involves strong Python development and experience with various AI and machine learning frameworks, focusing on ...

Senior AI Software Engineer

Denver, CO · On-site

$126K - $166K/yr

The Opportunity The Generative AI Innovation Team is transforming how Litera-and its clients-leverage data for competitive advantage. As a Senior AI Engineer, you will play a critical role in shaping ...

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Senior Generative Ai Engineer information

What does a senior generative AI engineer do?

A Senior Generative AI Engineer designs, develops, and implements advanced artificial intelligence models, particularly those focused on generating content such as text, images, or audio. They work with large datasets, build and fine-tune generative models like GPT or diffusion models, and oversee the deployment of these systems into production environments. Additionally, they collaborate with cross-functional teams to integrate AI capabilities into products, optimize model performance, and ensure ethical AI practices are followed.

What are the key skills and qualifications needed to thrive as a senior generative AI engineer, and why are they important?

To thrive as a Senior Generative AI Engineer, you need deep expertise in machine learning, deep learning, and natural language processing, typically backed by an advanced degree in computer science or related fields. Proficiency in frameworks like TensorFlow or PyTorch, experience with cloud platforms (e.g., AWS, Azure), and familiarity with large language models are essential, along with relevant certifications. Strong problem-solving skills, creativity, and effective communication set standout engineers apart in this role. These skills and qualities are crucial for designing innovative AI solutions, collaborating across teams, and advancing the capabilities of generative models in real-world applications.

What are some of the unique challenges senior generative AI engineers face when deploying models in production environments?

Senior Generative AI Engineers often encounter challenges such as ensuring model reliability, addressing biases in generated outputs, and managing the significant computational resources required for deployment. There's also a strong need to collaborate with cross-functional teams, including data engineers, product managers, and domain experts, to ensure the solutions align with business goals and maintain user trust. Balancing innovation with ethical considerations and scalability is crucial in this fast-evolving field.

What is the difference between Senior Generative Ai Engineer vs Machine Learning Engineer?

AspectSenior Generative Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with generative modelsBachelor's/Master's in CS, Data Science, or related; strong ML fundamentals
Work EnvironmentResearch and development focused, often in AI startups or tech companiesData analysis, model development, often across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech, finance, healthcare, and other sectors utilizing ML solutions

The main difference is that Senior Generative Ai Engineers specialize in developing and optimizing generative models like GPT or GANs, focusing on AI creativity and content generation. Machine Learning Engineers have a broader scope, working on various ML algorithms and applications across multiple industries. Both roles require strong technical skills, but the Senior Generative Ai Engineer's expertise is more specialized in generative AI technologies.

What are the most commonly searched types of Generative Ai Engineer jobs in Colorado?

The most popular types of Generative Ai Engineer jobs in Colorado are:

What are popular job titles related to Senior Generative Ai Engineer jobs in Colorado?

For Senior Generative Ai Engineer jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Senior Generative Ai Engineer jobs in Colorado look for?

The top searched job categories for Senior Generative Ai Engineer jobs in Colorado are:

What cities in Colorado are hiring for Senior Generative Ai Engineer jobs?

Cities in Colorado with the most Senior Generative Ai Engineer job openings:

Infographic showing various Senior Generative Ai Engineer job openings in Colorado as of August 2026, with employment types broken down into 74% Full Time, 23% Part Time, and 3% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.

Full-time

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GEI Consultants rating

7.6

Company rating: 7.6 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

284th of 453 rated engineering


Job description

Description
Your role at GEI.
The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained models and copilots, to support GEI's priority digital and AI initiatives. This role focuses on building, deploying, and integrating AI capabilities into business workflows in a secure, scalable, and maintainable manner.
The AI Engineer plays a hands-on role in active AI Solutions Factory use cases by implementing AI-based solutions, integrating enterprise data sources, and supporting solution reliability and performance. This role works closely with solution architects and platform teams to ensure AI solutions are production-ready, aligned with GEI standards, and capable of scaling across use cases.
Essential Responsibilities & Duties
  • Build and deploy AI-based solutions using pretrained models and Copilot technologies.
  • Design and implement prompt flows, plugins, and orchestrations using Copilot Studio and Azure Functions.
  • Integrate AI capabilities into business workflows and applications.
  • Integrate enterprise data sources securely, including APIs, Graph connectors, retrieval-augmented generation (RAG), and event-driven patterns.
  • Maintain and optimize Power BI dashboards that support AI-enabled workflows and insights.
  • Instrument AI solutions for telemetry, reliability, performance monitoring, and cost control.
  • Provide technical support and troubleshooting for deployed AI solutions.
  • Identify implementation risks and support mitigation strategies in collaboration with architecture and platform teams.

Minimum Qualifications
  • 4+ years of software engineering experience, with at least 1 year building Generative AI applications.
  • Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks.
  • Proficiency in at least one programming language such as Python, PySpark, R, or SQL.
  • Experience delivering Generative AI (LLM) solutions, preferably on Azure.
  • Familiarity with Azure AI library APIs, including GPT, Codex, and DALL• E, and other frameworks (e.g., Databricks Mosaic) for integrating Generative AI into business workflows.
  • Knowledge of big data technologies such as Spark and Databricks; familiarity with TensorFlow and PyTorch is a plus.
  • Knowledge of Azure cloud services, including Azure AI Platform, Azure Data Factory, Azure Synapse, and Azure Cognitive Services, and their integration with ML workflows.
  • Familiarity with AI ethics, bias mitigation, explainability techniques, and responsible AI practices.
  • Knowledge of security best practices for AI solutions, including data encryption, access control, and endpoint protection.
  • Prior experience implementing AI/ML solutions in professional services, engineering, or construction environments is a plus.
  • Azure or Databricks certifications (e.g., Azure AI Engineer Associate, Azure Solutions Architect Expert, Databricks ML Professional, Databricks Data Engineer Professional) are a plus.

We are GEI.
Some of the world's most pressing problems - from climate change to sustainable development, to critical infrastructure and the future of our energy supply - need our brightest and diverse minds working together to create safer, more resilient communities for tomorrow.
We are technical experts, collaborators, and entrepreneurs who draw from diverse backgrounds to solve our clients' most complex challenges.
With several offices across North America, we offer a range of engineering, science, and technical consulting services. Our range of expertise, project types, and culture make us the choice for top talent in the AEC industry. See all our office locations here .
Employee-owned. Employee-focused.
As an employee-owned company, our employees support our flat leadership structure, have a say in how our business operates and benefit from our financial success. We are committed to employee growth with career development opportunities, competitive total rewards, a well-being program, flexible work arrangements and more. Our company culture is driven by our 4 Cs - we are Client-Centered, Curious, Collaborative, and Community Minded - which support our focus on sustainability, safety, diversity, equity and inclusion. Get to know us better by visiting GEI's career site here .
GEI's Total Rewards Package Includes
  • Market-Competitive Compensation, including Eligibility for an Annual Performance Bonus
  • Pay Range For This Position: $110,000.00- $150,000.00/year
  • Comprehensive Benefits Program, including Medical, Dental, Vision, Life, Disability and More
  • Well-Being Program and Paid Parental Leave
  • Commuter Benefits
  • Hybrid Work Schedules and Cell Phone Stipends
  • GEI University (GEIU) with Continuing Education Assistance and Tuition Reimbursement
  • Connecting Conversation Program with a Focus on Professional Development and Opportunities for Advancement
  • Support and Financial Rewards for Publication Awards, Professional Dues, and Professional Licenses
  • Paid Holidays and Generous Paid Time Off Program
  • Rewards and Recognition
  • GEI-Funded Profit Sharing and 401(k)
  • Opportunity to be an Owner and Shareholder (Learn more here )
  • A Vibrant Culture that is Focused on Partnership, Sustainability, Giving Back to Our Communities and Diversity, Equity and Inclusion
  • And More...

PHYSICAL REQUIREMENTS
WORK ENVIRONMENT
Functional Demands:
Sedentary
x
Light
Medium
Other
Activity Level Throughout Workday (check one per row)
Physical Activity Requirements
Occasional
(0-35% of day)
Frequent
(33-66% of day)
Continuous
(67-100% of day)
Not Applicable
Sitting
x
Standing
x
Walking
x
Climbing
x
Lifting (floor to waist level) (in pounds)
x
Lifting (waist level and above) (in pounds)
x
Carrying objects
x
Push/pull
x
Twisting
x
Bending
x
Reaching forward
x
Reaching overhead
x
Squat/kneel/crawl
x
Wrist position deviation
x
Pinching/fine motor skills
x
Keyboard use/repetitive motion
x
Taste or smell (taste=never)
x
Talk or hear
x
Accurate 20/40
Very Accurate 20/20
Not Applicable
Near Vision
x
Far Vision
x
Yes
No
Not Applicable
Color Discrimination
Sensory Requirements
Minimal
Moderate
Accurate
Not Applicable
Depth perception
x
Hearing
x
Environment Requirements
Occupational Exposure Risk Potential
Reasonably Anticipated
Not Anticipated
Blood borne pathogens
x
Chemical
x
Airborne communicable diseases
x
Extreme temperatures
x
Radiation
x
Uneven surfaces or elevations
x
Extreme noise levels
x
Dust/particulate matter
x
Other (exposure risks):
Usual workday hours :
x
8
10
12
Other work hours
GEI is an AA/equal opportunity employer, including disabled and veterans.

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