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Ai Platform Engineer Jobs in Colorado (NOW HIRING)

Senior AI/ML Platform Engineer

Denver, CO · On-site

$107K - $147K/yr

The Senior AI/ML Platform Engineer will help build and operate the technical foundation required to move AI/ML capabilities from project-based implementations into governed, observable, production ...

AI Platform Operations Manager

Denver, CO · On-site

$54.25 - $74.25/hr

The DevOps Engineer, AI Platform is responsible for automating, deploying, and operating the infrastructure and delivery pipelines that support STACK's enterprise AI platform on Azure. This is a ...

... a Platform Engineer to design, build, and maintain the AWS infrastructure that underpins the IIA ... Build and maintain infrastructure for AI agent runtime environments for LangGraph agents via ...

... a Platform Engineer to design, build, and maintain the AWS infrastructure that underpins the IIA ... Build and maintain infrastructure for AI agent runtime environments for LangGraph agents via ...

AI OPS Engineer

Denver, CO · On-site

$71K - $96K/yr

The AI Automation Engineer will be the foundational builder for our Enterprise Operational AI Platform, bridging the gap between advanced multi-agent AI architecture and our core IT operations. Their ...

AI Ops Engineer II

Denver, CO · On-site

$100K - $137K/yr

The AI Automation Engineer will be the foundational builder for client's Enterprise Operational AI Platform, bridging the gap between advanced multi-agent AI architecture and our core IT operations. ...

CapTech is seeking a SaaS platform engineer to play a hands-on role in the engineering ... Lead automation initiatives (AI Agents, PowerShell, APIs, workflows) to streamline provisioning ...

... know Job Title AWS Platform Engineer Location: Denver, CO Contract duration 12 Skills ... AI agent runtime environments, including compute resources for Lang Graph agents deployed via Lang ...

Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build ...

Reports to: CEO The role We're hiring a senior full-stack engineer to build the next generation of Ombud's agentic AI platform. The work splits across two domains: building the agentic engine itself ...

Ombuddy Native: our next-generation agentic platform replacing the existing Chrome extension ... We expect our engineers to use AI as a force multiplier on their own output. * Strong intuition for ...

Reports to: CEO The role We're hiring a senior full-stack engineer to build the next generation of Ombud's agentic AI platform. The work splits across two domains: building the agentic engine itself ...

Lead AI Engineer

Denver, CO · On-site

$147K - $202K/yr

A day in the life The Lead AI Engineer builds production AI platform capabilities that transform Prologis building, project, asset, and operational data into reusable solutions for construction ...

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 ...

Lead AI Engineer

Denver, CO · On-site

$147K - $202K/yr

A day in the life The Lead AI Engineer builds production AI platform capabilities that transform Prologis building, project, asset, and operational data into reusable solutions for construction ...

Showing results 21-40

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:

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 AI/ML Platform Engineer

bp

Denver, CO • On-site

$107K - $147K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 6 days ago


BP rating

5.5

Company rating: 5.5 out of 10

Based on 192 frontline employees who took The Breakroom Quiz

74th of 87 rated oil and gas companies


Job description

Job Family Group:
IT&S Group
Job Description:
bpx energy, a major oil and gas producer in the United States, demonstrates its expertise in unconventional gas, including shale, to deliver hydrocarbon production and technical knowledge worldwide. With operations in Texas and Louisiana, our US onshore business has become both a best-in-class oil and gas producer and a leader in reducing methane emissions. As part of BP, a global industry leader, we champion a high-energy, high-intensity environment built on accountability, collegiality, and empowerment.
Role Overview
bpx energy is building an enterprise AI capability that can scale safely and deliver real operational value. The Senior AI/ML Platform Engineer will help build and operate the technical foundation required to move AI/ML capabilities from project-based implementations into governed, observable, production-grade enterprise capabilities.
This is a hands-on platform engineering role focused on the systems, patterns, environments, controls, and automation required for production AI/ML delivery. The role will work across Palantir, Snowflake, Databricks, AWS, and related AI/ML services to create the "paved roads" that allow teams to be versatile and quick-moving.
This role will not focus on building one-off AI use cases. It is focused on making AI/ML engineering repeatable, reliable, secure, and scalable across the enterprise.
What You'll Do
Build, operate, and evolve AI/ML platform capabilities across Palantir, Databricks, AWS, MLflow, model registries, model serving, feature management, vector stores, and related services.
  • Create reusable platform patterns for model development, deployment, serving, monitoring, access controls, and production support.
  • Implement CI/CD, infrastructure automation, environment management, secrets management, access controls, and deployment templates for AI/ML workloads.
  • Partner with security, infrastructure, data, and enterprise architecture teams to ensure AI/ML platforms are secure, observable, auditable, and operationally reliable.
  • Support batch, real-time, streaming, and API-based model deployment patterns.
  • Establish standard engineering patterns for experiments, notebooks, jobs, pipelines, model serving, and production promotion.
  • Help define platform usage standards, tiered access models, cost controls, observability requirements, and operational support patterns.
  • Ensure AI/ML workloads are designed for reliability, scalability, performance, maintainability, and governance.
  • Support future federated AI/ML engineering by creating reusable templates, reference architectures, and enablement materials for domain teams.

Minimum Requirements
  • Bachelor's degree in engineering, computer science, information systems, or related field, or equivalent work experience.
  • Proven experience building, operating, or enabling production AI/ML engineering platforms in a cloud environment.
  • Hands-on experience with at least one modern AI/ML platform such as Databricks, AWS SageMaker, MLflow, Azure ML, Vertex AI, or equivalent.
  • Practical experience with CI/CD, infrastructure automation, environment management, secrets management, access controls, and production deployment patterns.
  • Experience supporting model development and deployment workflows beyond experimentation or notebooks.
  • Strong understanding of cloud-native architecture, APIs, containers, compute patterns, storage patterns, and runtime observability.
  • Ability to build reusable engineering patterns, templates, reference architectures, and platform "paved roads."
  • Experience partnering with data engineering, security, infrastructure, and architecture teams to move AI/ML workloads into governed production environments.
  • Proven track record to troubleshoot platform, deployment, performance, integration, or reliability issues in sophisticated technical environments.

Strongly Preferred
  • Databricks platform engineering experience, including workspaces, clusters/serverless, Unity Catalog, MLflow, model serving, jobs/workflows, permissions, and cost controls.
  • AWS experience with IAM, networking, security groups, S3, Lambda, ECS/EKS, API Gateway, Bedrock, SageMaker, or related services.
  • Experience supporting regulated, safety-sensitive, industrial, energy, financial, healthcare, or other high-consequence operating environments.
  • Experience with platform cost management and workload optimization.
  • Experience creating reusable platform enablement materials for engineers, data scientists, or domain technical teams.

Additional Role Scope Information
This is not a traditional software engineering, application development, BI, or data engineering role. It is also not a notebook-only experimentation role.
This role is not a fit for candidates whose experience is primarily:
  • Traditional application/software engineering without hands-on AI/ML platform, MLOps, or ModelOps experience.
  • Generic cloud or DevOps engineering without production AI/ML deployment or platform experience.
  • Data science experimentation without responsibility for production deployment patterns.
  • Data pipeline engineering without exposure to model development, model serving, or AI/ML lifecycle operations.
  • Single-use-case delivery without experience creating reusable platform capabilities.

Adjacent backgrounds are welcome when the candidate can demonstrate direct experience helping AI/ML workloads move into governed, observable, production-grade environments.
Salary and Benefits
We offer a reward and wellbeing package to enable your work to fit with your life. These can include, but not limited to, access to health, vision and dental insurance, flexible working schedule, paid time off policy, discretionary annual bonus program, long-term incentive program, and a generous 401K matching program. How much do we pay (Base)? $135,000 - $175,000
*Note that the pay range listed for this position is a good faith and reasonable estimate of the range of possible base compensation at the time of posting.
Travel Requirement:
Negligible travel should be expected with this role
Relocation Assistance:
Relocation may be negotiable for this role
Remote Type:
This position is a hybrid of office/remote working
Skills:
Cloud Platforms, Cloud Platforms, Collaboration, Communication, Configuration management and release, Continuous deployment and release, Creating a high performing team, Database Design, Digital Project Management, Documentation and knowledge sharing, Emerging technology monitoring, Facilitation, Information Security, Mentoring, Metrics definition and instrumentation, NoSql data modelling, Problem Solving, Relational Data Modelling, Risk Management, Scripting, Secure development, Service operations and resiliency, Software Design and Development, Solution Architecture, Source control and code management {+ 5 more}
Legal Disclaimer:
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, socioeconomic status, neurodiversity/neurocognitive functioning, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp's recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please contact us.
If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.

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