AI Engineer Salary in Denver — 2026 BLS Data
Salary distribution
Percentile breakdown of AI Engineer base salaries in Denver.
The $152K median base for an AI Engineer in Denver is a meaningful number — but only if you understand what it’s actually measuring. BLS OEWS does not yet publish a standalone “AI Engineer” occupation code. The closest mapped categories are Software Developers (SOC 15-1252) and Data Scientists (SOC 15-2051). The May 2024 OEWS national median for software developers is $133,080; for data scientists it’s $112,590. Denver’s AI engineer market sits above both because the role demands skills that overlap both tracks — ML model deployment, LLM integration, vector databases, inference optimization — in a market where that combined skillset is scarce relative to demand. BLS OEWS May 2024 data shows that computer and mathematical occupations in the Denver-Aurora-Centennial metro averaged $60.06/hour, compared to $48.82 nationally for the same broad group — a 23% premium that reflects Denver’s above-average concentration of high-paying tech and aerospace roles. The AI engineer segment sits at the top of that distribution, not the middle.
The $118K P25 to $232K P90 range — a spread of more than $114K inside one city — tells you there is no single Denver AI engineer market. There are at least three, and which one you’re playing in matters more than any single percentile.
How Denver AI Engineer salaries compare to other tech hubs
Denver occupies a legitimate second tier in the US AI engineer market. It pays well above the national median but sits clearly below San Francisco, Seattle, and New York.
San Francisco and San Jose remain the compensation ceiling for AI roles. A mid-level AI engineer (3-5 years, generative AI focus) at a frontier lab or hyperscaler in SF runs $180K-$230K base with $60K-$120K in annualized equity, putting total comp in the $260K-$380K range. That is a real gap. But the COL premium is equally real — San Francisco’s composite COL index sits around 178, nearly 60% higher than Denver’s 112.
Seattle, driven by Amazon, Microsoft, and their ML-platform teams, lands $165K-$210K base for comparable AI engineering roles. The no-state-income-tax advantage in Washington meaningfully lifts take-home pay relative to Colorado’s 4.4% flat income tax, though the gap is smaller than the California comparison.
Austin runs $140K-$175K base for mid-level AI engineers at tech companies with engineering offices there (Dell, Apple, Oracle, Tesla AI). The COL index differential versus Denver is modest — Austin is around 119-122 — so the salary gap maps roughly to Austin being a softer market for pure AI/ML skills versus Denver’s aerospace and defense pipeline.
Denver at $152K median base closes to within 10-15% of Seattle on cash, beats Austin, and beats the national software developer median by nearly 14%. Once you adjust for COL, a $152K Denver salary has the purchasing power of roughly $242K in San Francisco. The range kore1 places Denver AI engineers in — $150K-$190K base with $185K-$250K total comp — is consistent with multiple data sources and reflects a market that is competitive without being irrational.
What the median hides: the three Denver AI engineer markets
The single most important thing to understand about Denver AI compensation is that the market is actually three distinct sub-markets that look like one in aggregate data.
Defense and aerospace AI. Colorado brought in $22.8 billion in federal aerospace funding in 2024, according to the Colorado Office of Economic Development and International Trade — a record. That money flows through Lockheed Martin Space, Ball Aerospace (now BAE Systems), Palantir (which maintains a major Denver presence), Leidos, and dozens of smaller primes. These roles require or strongly prefer security clearances. A TS/SCI clearance typically adds $15,000-$30,000 to base salary across all levels. AI engineers building computer vision systems for satellite imagery analysis or resilient ML infrastructure for edge deployment in these organizations earn $130K-$190K base at mid-level, without the equity upside of startup or hyperscaler roles. The floors are higher and the ceilings are lower.
Enterprise and cloud AI. Denver is CBRE’s eighth-ranked North American tech talent market, with 129,040 tech workers as of 2023 (up 12.6% from 2018). Oracle, Salesforce, Twilio, and a cluster of financial services companies (Charles Schwab moved its headquarters to Westlake, Texas, but maintains significant Denver engineering) hire AI engineers for production ML systems, recommendation engines, and LLM-powered product features. These roles typically pay $140K-$185K base at mid-level, with bonuses of 10-15% and RSU grants that vest over four years. This is the bulk of the market and where the $152K median lives.
Venture-backed and growth-stage startups. Denver and Boulder form a connected startup corridor with a real VC ecosystem — Techstars was founded here, and the area has produced companies like Zayo, Opendoor, and Ibotta. AI-native startups at Series A-C often pay $130K-$160K base with equity grants of 0.1-0.5% for early employees. The equity is illiquid and speculative, but it represents the realistic upside lever that neither defense nor public-company roles offer at the same magnitude.
The median of $152K averages across all three. It tells you nothing about which market you’re actually in or what ceiling is available to you.
Total compensation breakdown
For a mid-level AI engineer at a Denver enterprise or cloud company (3-5 years experience, generative AI or MLOps focus), the compensation structure looks approximately like this:
- Base salary: $152K. This is the BLS-tracked figure and what hits your paycheck. Denver pay bands at established companies are usually set using national survey data and geographic differentials — expect less negotiating room on base than you’d have at a coastal company’s posted range.
- Annual cash bonus: $18K. Most enterprise tech employers in Denver pay 10-15% of base as a performance bonus. Defense contractors sometimes structure this as a separate incentive plan tied to contract awards, which creates real variance year-to-year.
- Annualized equity: $22K. At a public company, this is a four-year RSU grant divided by four. A typical mid-level grant in this market runs $80K-$100K over four years. At a pre-IPO startup, the nominal value is higher but illiquidity discounts apply — mentally mark down your startup equity by 60-70% unless there’s a credible near-term liquidity event.
Total: approximately $192K at a public or late-stage company. At a defense contractor without equity: $165K-$175K all-in, with the clearance premium baked into base. At a Series B AI startup: $145K-$160K base plus equity that could be worth nothing or worth $500K+ depending on the outcome.
Signing bonuses in Denver are more common for AI roles than for general software engineering positions — the skills gap is real enough that companies competing for LLM-platform or MLOps talent regularly offer $15K-$30K signing as a close lever.
Cost-of-living adjusted value
Denver’s COL index of 112 means living costs run about 12% above the national average. That is moderate by the standards of the tech cities that dominate AI job postings. The breakdown matters: housing carries the most weight, and Denver’s median rent for a one-bedroom ($1,850-$2,200 in the metro) is substantially below San Francisco ($3,500-$4,200) and Seattle ($2,100-$2,600), and below Austin’s recent surge ($1,700-$2,100). Groceries and transportation in Denver run close to or slightly above the national average.
On a COL-adjusted basis, a $152K Denver base has the purchasing power equivalent of:
- About $241K in San Francisco (COL 178)
- About $188K in Seattle (COL 145)
- About $128K at the national average (COL 100)
- About $143K in Austin (COL 119)
The Denver number looks most attractive on a COL-adjusted basis against San Francisco and Seattle. Against Austin, the gap is small in either direction. Against a fully remote role benchmarked to national pay scales, Denver base salaries are genuinely above what the COL differential would predict — the market isn’t discounting you just because you’re not in a coastal city.
Colorado has a 4.4% flat income tax rate. There is no local Denver income tax. Washington State’s zero income tax does create a meaningful take-home advantage for Seattle workers at identical salary levels — roughly $5,000-$8,000 per year on a $152K salary after federal deductions. Factor that in when directly comparing Denver and Seattle offers.
Three negotiation levers that work in Denver
The Denver AI engineer market is tight enough that candidates with real production experience — LLM fine-tuning, RAG pipeline architecture, MLOps at scale — have real leverage. Three tactics that translate to money:
1. Use the clearance premium as a benchmark, not a ceiling. Even if you’re interviewing at a company that does not require clearances, the fact that cleared AI engineers in Denver command $15K-$30K above market for similar technical work sets a floor that is useful in negotiations. If you have a clearance and you’re interviewing at a non-defense company, you can frame it as: “I’m evaluating offers that include positions in the defense sector where the premium for my clearance and ML background is $X — I’m interested in this role for the civilian-sector product work, but I need the offer to reflect where the market is.” That’s a legitimate data point, not a bluff.
2. Negotiate the equity grant size, not just the total comp headline. At enterprise tech companies in Denver, equity grants are sometimes smaller than what equivalent-level offers show at coastal companies benchmarked to the same level. If you have a competing offer with a larger grant, bring it. The most productive framing is not “match this offer” but “I’d like to understand whether there’s flexibility in the initial RSU grant — I’ve seen grants in the $100K-$130K range for this level elsewhere.” Managers can often increase equity grants with less internal friction than raising base above the published band.
3. Push for a performance review at 12 months, not 18. The standard review cycle at many Denver employers is 18 months before the first raise or equity refresh conversation. In a market where AI engineering compensation moved roughly 15-20% upward between 2023 and 2025, being locked into an 18-month band means you lose ground against current market rates. Ask during offer negotiation — not after signing — whether a 12-month check-in with a defined compensation review is possible. Framing: “Given how fast this space is moving, I’d like to make sure there’s a formal mechanism to revisit compensation after 12 months rather than waiting for a standard review cycle.” Most reasonable hiring managers will accommodate that ask, and it costs them nothing to agree to in the moment.
Data caveats
The figures on this page triangulate BLS OEWS May 2024 data, Glassdoor and Levels.fyi reported salaries for Denver AI and ML engineers, and placement data published by specialized recruiters (KORE1 and Signify Technology) active in the AI engineering market. Several limitations are worth naming directly:
BLS OEWS does not have an “AI Engineer” occupation code. SOC 15-1252 (Software Developers) and SOC 15-2051 (Data Scientists) are the closest statutory categories, and AI engineers are distributed across both depending on how each employer classifies the role. The percentiles on this page are market estimates derived by applying Denver’s documented computer-and-mathematical occupation premium to national BLS benchmarks and calibrating against reported salary data from multiple aggregators — not a single table pull from one source.
Equity is understated in all base-salary data. BLS tracks wages, not equity grants. At enterprise tech companies and well-funded startups, annualized equity adds 10-30% to total comp. Pre-IPO equity is harder to value and excluded from every figure on this page.
The “AI engineer” title is not standardized. A job posting using this title at one company may be substantially a senior data scientist role; at another it may be an MLOps engineer; at another it may be a prompt engineer or LLM application developer. The scope and seniority implied by the title varies widely enough that two people with the same title at different Denver employers can be doing fundamentally different work at different market rates.
Data has a lag. May 2024 OEWS data reflects wages paid in 2024. AI engineering compensation has been among the fastest-moving segments of the tech market — job postings requiring generative AI skills grew 163% between 2024 and 2025 according to market tracking data — which means the 2024 figures likely understate current (2026) market rates by 8-15% for roles with active generative AI scope.
Supplement these numbers with current job postings on Levels.fyi and Colorado’s own salary transparency — Colorado’s Equal Pay for Equal Work Act requires employers with Colorado workers to include pay ranges in job postings, making posted ranges a useful real-time calibration tool that most other states cannot offer. For any active job search, a posted range plus the BLS anchor gets you within 8-10% of a well-informed negotiating position.