ZipRecruiter

Log In

1

Ai Platform Engineer Jobs in Colorado (NOW HIRING)

Focused

Senior Platform Engineer

Denver, CO · On-site

$130K - $180K/yr

Platform Engineering & Infrastructure * Augment existing infrastructure with with integrated ... Experience with AI/ML model deployment and monitoring in production environments Leadership ...

Kiewit Corporation

Sr AI Engineer

Lone Tree, CO · On-site +1

$103K - $141K/yr

This engineer independently delivers complex platform capabilities, mentors junior engineers, and ... Design, develop, and deploy reusable AI platform services and backend APIs. * Build scalable ...

Apex Systems

OMS Platform Engineer

Broomfield, CO · On-site

Job#: 3043367 OMS Platform Engineer Location: Remote, United States Role Overview This role ... By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails ...

Campminder

Senior AI Engineer

Boulder, CO · On-site +1

$108K - $148K/yr

We are looking for a Senior AI Engineer to join our AI Platform team, which owns AI enablement internally across Campminder, and externally to our customers. As a senior engineer on the team, you ...

Campminder

Senior AI Engineer

Boulder, CO · On-site +1

$108K - $148K/yr

We are looking for a Senior AI Engineer to join our AI Platform team, which owns AI enablement internally across Campminder, and externally to our customers. As a senior engineer on the team, you ...

previous page

Showing results 41-60

All JobsAi Platform Engineer JobsAi Platform Engineer Jobs in Colorado

Ai Platform Engineer information

See Colorado salary details

$34

$67

$99

How much do ai platform engineer jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for ai platform engineer in Colorado is $67.25, according to ZipRecruiter salary data. Most workers in this role earn between $53.08 and $77.60 per hour, depending on experience, location, and employer.

What is an AI Platform Engineer?

AI Platform Engineers are technology professionals who design, build, and maintain the infrastructure that supports the development, deployment, and scaling of artificial intelligence (AI) and machine learning (ML) models. They work closely with data scientists and software engineers to ensure that AI solutions can run efficiently and securely in production environments. Their responsibilities often include managing cloud or on-premises platforms, automating workflows, and implementing best practices for model versioning, monitoring, and resource optimization.

How does an AI Platform Engineer typically collaborate with data scientists and software engineers in a project environment?

AI Platform Engineers often serve as a bridge between data scientists and software engineers, ensuring that machine learning models are seamlessly integrated into scalable, production-ready systems. They work closely with data scientists to understand model requirements and deployment needs, and with software engineers to embed these models within applications and services. This collaboration involves frequent communication, joint troubleshooting, and participation in code reviews to maintain a robust and efficient AI infrastructure.

What are the key skills and qualifications needed to thrive as an AI Platform Engineer, and why are they important?

To thrive as an AI Platform Engineer, you need strong programming skills (especially in Python and Java), a background in computer science or related fields, and experience with machine learning frameworks. Familiarity with cloud platforms (like AWS, Azure, or GCP), containerization tools (Docker, Kubernetes), and CI/CD systems is typically required, along with certifications such as Google Cloud Professional Machine Learning Engineer. Excellent problem-solving, collaboration, and communication skills help you integrate AI solutions across teams and projects. These competencies ensure the efficient development, deployment, and maintenance of scalable AI systems in dynamic production environments.

What is the difference between Ai Platform Engineer vs Data Engineer?

AspectAi Platform EngineerData Engineer
CredentialsBachelor's in CS, AI, or related; experience with cloud platformsBachelor's in CS, Data Science, or related; experience with databases and ETL tools
Work EnvironmentDeveloping AI infrastructure, deploying ML models, working with cloud servicesBuilding data pipelines, managing data storage, ensuring data quality
Industry UsageTech companies, AI startups, cloud providersFinance, healthcare, e-commerce, any data-driven industry

While both roles involve working with data and cloud platforms, Ai Platform Engineers focus on building and maintaining AI infrastructure and deploying machine learning models. Data Engineers primarily develop data pipelines and manage data storage. The roles often collaborate but serve different core functions within AI and data ecosystems.

How to become an AI platform engineer?

To become an AI platform engineer, you should have a strong background in computer science, software engineering, or related fields, with expertise in machine learning frameworks, cloud computing, and programming languages like Python or Java. Gaining experience with AI tools, data management, and infrastructure deployment is essential, often supported by certifications in cloud platforms such as AWS or Azure. Building a portfolio of projects and staying updated on AI and DevOps practices can also enhance your qualifications.

What does an AI platform engineer do?

An AI platform engineer designs, develops, and maintains the infrastructure and tools needed to deploy and manage artificial intelligence models at scale. They work with cloud services, programming languages, and machine learning frameworks to ensure efficient model training, deployment, and monitoring in production environments.

What is the salary of AI platform engineer?

The salary of an AI platform engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and machine learning may earn higher compensation.

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

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

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

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

What cities in Colorado are hiring for Ai Platform Engineer jobs?

Cities in Colorado with the most Ai Platform Engineer job openings:

Ai Platform Engineer jobs near you
Infographic showing various Ai Platform Engineer job openings in Colorado as of August 2026, with employment types broken down into 58% Full Time, 39% Part Time, 1% Temporary, and 2% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution, with an average salary of $139,879 per year, or $67.2 per hour.

Senior Platform Engineer

Focused

Denver, CO • On-site

$130K - $180K/yr

Full-time

Posted 14 days ago

Job description

Who we are:

At Focused, we move quickly to deliver quality software that achieves client outcomes and meets their customer's needs. We strategically partner with our clients to leverage our expertise in design and software, while our clients bring their own domain expertise. We work with a variety of clients from different industries, collaborating as we get new products to market, modernizing legacy systems, or helping teams learn the skills they need to be successful.   

Our values:

  • Listen first • We are experts in product practices but life long learners in the domain of our customers. We research, collaborate, and understand. 
  • Learn why • We ask questions and talk to users to understand problem spaces, objectives, and goals, which allows us to deeply invest and drive towards the outcomes of our clients. 
  • Love your craft • We love diving into a variety of domains and solving problems.  We take pride in delivering value, in communicating progress, and guiding our clients to success.

We are seeking an experienced Senior Platform Consultant to help organizations implement, optimize, and scale their infrastructure. 

Key Responsibilities:

Platform Engineering & Infrastructure

  • Augment existing infrastructure with with integrated observability solutions
  • Implement Infrastructure as Code (IaC) solutions using Terraform, Pulumi, CloudFormation, etc.
  • Architect and manage Kubernetes clusters with comprehensive monitoring and logging
  • Build CI/CD pipelines with embedded observability and automated testing

Site Reliability Engineering (SRE)

  • Establish and maintain Service Level Indicators (SLIs), Objectives (SLOs), and Agreements (SLAs)
  • Implement error budgets, toil reduction strategies, and capacity planning
  • Support incident response procedures and post-mortem processes

Cloud & DevOps Engineering

  • Deploy and manage observability infrastructure across AWS, GCP, and Azure
  • Establish security, compliance, and governance frameworks for telemetry data
  • Experience automating Agent Evaluations in CI/CD pipelines and observability backends.

Required Qualifications:

Platform Engineering & DevOps

  • 3+ years of Platform Engineering or DevOps experience 
  • Proficiency with Infrastructure as Code tools (Terraform, Pulumi, CloudFormation, CDK)
  • Strong experience with CI/CD platforms (GitHub Actions, GitLab CI, Jenkins, ArgoCD)

Cloud & Infrastructure

  • Hands-on experience with major cloud providers (AWS, GCP, Azure) and their observability services
  • Experience with container technologies (Docker, Podman) and container registries
  • Knowledge of networking, security, load balancing, and distributed systems concepts

Site Reliability Engineering

  • Experience implementing SRE practices including error budgets and toil metrics
  • Proficiency in incident management, on-call procedures, and post-mortem culture
  • Experience with capacity planning, performance optimization, and scalability design

Programming & Automation

  • Proficiency in multiple programming languages preferred (Go, Python, Java, Node.js, Rust)
  • Strong scripting and automation skills (Bash, Python, PowerShell)
  • Understanding of software engineering best practices and testing methodologies

Core Observability & OpenTelemetry

  • Experience in observability, monitoring, and distributed systems
  • Hands-on experience with OpenTelemetry ecosystem, including SDKs, APIs, and specifications
  • Proficiency with OpenTelemetry Collector configuration, processors, exporters, and receivers
  • Strong understanding of telemetry data models, semantic conventions, and instrumentation best practices

Preferred Qualifications (Exceptional Candidates)

AI & Agentic Frameworks

  • Understanding of Large Language Models (LLMs) and their application in DevOps
  • Knowledge of vector databases, embeddings, and retrieval-augmented generation (RAG)
  • Experience with AI/ML model deployment and monitoring in production environments

Leadership & Communication

  • Strong technical writing and documentation skills
  • Ability to present complex technical concepts to diverse stakeholders
  • A passion for knowledge sharing

Key Competencies

  • Systems thinking and ability to design holistic observability solutions
  • Strong analytical and troubleshooting skills for complex distributed systems
  • Curiosity about emerging technologies, particularly AI applications in operations
  • Adaptability to rapidly evolving cloud-native and observability technologies
  • Collaborative mindset with focus on enabling developer productivity and system reliability

What to know before you apply: 

  • This role will require being in the Denver office three days per week and up to 20% travel within the United States.
  • Focused is unable to sponsor or take over sponsorship of the employment Visa process at this time.
  • The Denver base salary range for this role is $130,000 - $180,000.

Apply