Interested in this AI/ML Engineer role at Go West IT?
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About This Role
APPLY DIRECTLY VIA OUR COMPANY CAREERS PAGE: https://www.gowestit.com/careers/#job-2694224
As a leading MSSP in Colorado, Go West IT is the trusted guide to the digital frontier. Our mission is to help companies benefit from technology by expertly guiding them to opportunities and protecting them from harm. We do this by providing a team of trusted guides with the knowledge, skills, and expertise needed to navigate this constantly changing landscape. Our entire team is continually building their knowledge base, keeping us ahead of the technology curve and helping us succeed at our mission.
As an AI & Automation Engineer, you will be a member of the MSP Team, helping transform how we deliver technology services by designing, building, and maintaining AI-powered solutions and intelligent automations. This role combines traditional automation engineering with modern AI engineering to improve internal operations, increase efficiency, and enhance the client experience.
You will develop AI agents, LLM-powered workflows, automation scripts, integrations, and cloud-native solutions that eliminate repetitive work, accelerate service delivery, and enable data-driven decision making. You'll work closely with engineering, service desk, account management, and leadership teams to identify opportunities where automation and AI can deliver measurable business value.
What you can expect from us:
- Opportunity to be an integral part of an organization on the cutting edge of AI and technical innovation
- A fast-paced environment where every day brings new technical challenges and opportunities
- Opportunity to research, experiment with, and implement emerging AI technologies
- A commitment to professional development with resources to continuously learn and grow
- Collaboration with an exceptionally talented and supportive technical team
- Hybrid work environment
- Company-paid events and employee recognition programs
- Competitive salary range of $145,000-$175,000 annually along with comprehensive benefits including PTO, medical, dental, vision, life, disability, and 401(k) with generous company match
What we will expect from you:
- Consistently demonstrate Go West's Core Values
- Passion for solving complex business problems through automation and AI
- Strong ownership mentality with the ability to independently drive projects from concept through deployment
- Excellent written and verbal communication skills
- Ability to explain technical AI concepts to non-technical audiences
- Strong analytical thinking and curiosity for emerging technologies
- Exceptional documentation habits and commitment to maintainable code
- Ability to prioritize multiple initiatives while managing stakeholder expectations
- Continuous improvement mindset with enthusiasm for learning new tools and technologies
What you will be doing:
AI Engineering:
- Design, develop, and deploy AI-powered solutions that improve internal operations and client service delivery
- Build and maintain AI agents using Claude and other modern LLM technologies
- Develop prompt engineering standards, reusable prompt libraries, and AI workflows
- Create internal AI tools that increase technician productivity and automate repetitive work
- Evaluate emerging AI technologies and recommend adoption where appropriate
- Develop retrieval-augmented generation (RAG) solutions utilizing company documentation and knowledge bases
- Build AI-assisted reporting, knowledge management, and operational tools
- Establish and maintain AI governance frameworks, testing standards, monitoring processes, and security controls to ensure all AI solutions follow industry best practices and protect internal and client data throughout the AI lifecycle
- Ensure all AI solutions follow approved governance policies, access controls, auditability requirements, and secure-by-design principles throughout the development lifecycle
Automation Engineering:
- Develop, test, and deploy automation scripts across business systems and managed service platforms
- Build integrations between PSA, RMM, Microsoft 365, Azure, security platforms, and other business applications
- Develop PowerShell and API-driven automation for Windows, macOS, Linux, and cloud environments
- Automate software deployment, monitoring, remediation, and infrastructure management
- Improve existing automation frameworks and identify new automation opportunities across the organization
Cloud & DevOps:
- Develop and maintain Azure Functions, Logic Apps, Automation Accounts, and other cloud-native services
- Build and maintain CI/CD pipelines using Azure DevOps
- Manage Git repositories, branching strategies, code reviews, and release processes
- Maintain secure development practices including secrets management and Key Vault integration
- Monitor production AI and automation solutions for reliability and performance
Collaboration & Innovation:
- Partner with technical teams to identify automation opportunities
- Work alongside leadership to prioritize AI initiatives with measurable ROI
- Document standards, architecture, and implementation procedures
- Participate in architecture discussions and continuous improvement initiatives
- Research and prototype emerging AI technologies to keep Go West at the forefront of innovation
Qualifications we require from you:
- 3+ years of experience developing automation solutions in a professional IT environment
- Experience working within a Managed Services Provider (MSP) environment
- Advanced PowerShell scripting experience
- Strong experience building integrations using REST APIs and Microsoft Graph
- Experience using Azure DevOps for source control, project management, and CI/CD pipelines
- Experience using Git, branching strategies, pull requests, and modern source control practices
- Required experience using Claude and Claude Code
- Experience designing, deploying, and supporting solutions within Microsoft Azure
- Strong understanding of cloud security best practices
- Experience with Azure OpenAI and prompt engineering
- Experience integrating AI solutions with Microsoft 365 (Teams, SharePoint, Outlook)
- Experience with DLP policies and data governance
- Background in business process automation or systems integration
- Knowledge of security, compliance, and responsible AI practices
- Experience troubleshooting complex automation and integration issues
- Authorization to work in the United States
Preferred skills from you:
- 5+ years of MSP experience
- Experience building AI agents and agentic workflows
- Experience with Model Context Protocol (MCP)
- Experience integrating LLMs into production workflows
- Experience with vector databases and Retrieval Augmented Generation (RAG)
- Experience with Azure AI Services, Azure OpenAI, or similar AI platforms
- Experience with Python in addition to PowerShell
- Experience with Microsoft Power Platform
- Knowledge of containerization
- Experience with infrastructure as code
- Familiarity with Power BI and data visualization
- Microsoft Certified: DevOps Engineer Expert
- AI-related certifications or equivalent demonstrated experience
- ITIL 4 Foundation Certification
Application deadline: 10/16/2026
Pay: $145,000.00 - $175,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Employee assistance program
- Flexible schedule
- Flexible spending account
- Health insurance
- Health savings account
- Life insurance
- Paid time off
- Professional development assistance
- Retirement plan
- Vision insurance
Application Question(s):
- Are you currently located within the state of Colorado?
Experience:
- developing automation solutions: 3 years (Required)
- Managed Services: 3 years (Required)
- Claude/Claude Code: 1 year (Required)
- Azure OpenAI: 1 year (Required)
License/Certification:
- ITIL Certification (Preferred)
Location:
- Greenwood Village, CO 80111 (Preferred)
Ability to Commute:
- Greenwood Village, CO 80111 (Required)
Work Location: Hybrid remote in Greenwood Village, CO 80111
Salary Context
This $145K-$175K range is below the median for AI/ML Engineer roles in our dataset (median: $176K across 1540 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Go West IT, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,000 based on 11,857 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($160K) sits 25% below the category median. Disclosed range: $145K to $175K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Go West IT AI Hiring
Go West IT has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Greenwood Village, CO, US. Compensation range: $175K - $175K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
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