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About This Role
Why Work for Frontier Airlines?
At Frontier, we believe the skies should be for everyone. We deliver on this promise through our commitment to Low Fares Done Right. This is more than our tagline - it’s our driving philosophy. Every member of Team Frontier has an important role to play in bringing this vision to life. Our successful business model allows travelers to take advantage of our fast-growing route network while our bundled and unbundled pricing options allow our customers to personalize their travel experience and only pay for the services they need – saving them money along the way.
What We Stand For
Low Fares Done Right is our mission and we strive to bring it to life every day. Our ‘Done Right’ promise means delivering not only affordable prices, but making travel friendly and easy for our customers. To do this, we put a great deal of care into every decision and action we take. We must be efficient with the use of our resources and make smart decisions about how we run our business. We must also innovate and be pioneers - we’re not afraid to try new things. While our business requires us to fly high in the air, we also consider ourselves down-to-earth in our approach, creating a warm and friendly experience that truly demonstrates Rocky Mountain Hospitality.
Work Perks
At Frontier, we like to think we’re creating something very special for our team members. Work is why we’re here, but the perks are nice too:
- Flight benefits for you and your family to fly on Frontier Airlines.
- Buddy passes for your friends so they can experience what makes us so great.
- Discounts throughout the travel industry on hotels, car rentals, cruises and vacation packages.
- Discounts on cell phone plans, movie tickets, restaurants, luggage and over 2,000 other vendors.
- Enjoy a ‘Dress for your Day’ business casual environment.
- Flexible work schedules that support work/life balance.
- Total Rewards program including a competitive base salary, short term incentives, long-term incentives, paid holidays, 401(k) plan, vacation/sick time and medical/dental/vision insurance that begins the 1st of the month following your hire date.
- We play our part to make a difference. The HOPE League, Frontier Airlines’ non-profit organization, is dedicated to providing employees financial assistance during catastrophic hardship.
Who We Are
Frontier Airlines is committed to offering ‘Low Fares Done Right’ to more than 100 destinations and growing in the United States, Canada, Dominican Republic and Mexico on more than 500 daily flights. Headquartered in Denver, Frontier’s hard-working aviation professionals pride themselves in delivering the company’s signature Low Fares Done Right service to customers. Frontier Airlines is the proud recipient of the Federal Aviation Administration’s 2018 Diamond Award for maintenance excellence and was recently named the industry’s most fuel-efficient airline by The International Council on Clean Transportation (ICCT) as a result of superior technology and operational efficiencies.
What Will You Be Doing?
We are seeking an accomplished Senior Director of Data & AI to shape, lead, and scale our enterprise data and artificial intelligence strategy. This role is responsible for building a modern data ecosystem grounded in Databricks, data mesh principles, and advanced analytics to power data-driven decisions across the organization. You will define the vision for how data is collected, transformed, governed, and democratized—ensuring the business can operate with trusted, timely, high-quality insights while accelerating our adoption of machine learning and AI-enabled capabilities.
Essential Functions
- Lead the development and evolution of scalable data platforms leveraging Databricks, Delta Lake, and Medallion Architecture (bronze, silver, gold) to ensure data lineage, quality, and long‑term scalability.
- Champion domain‑oriented ownership within a data mesh framework, enabling teams to design, build, and maintain high‑quality data products for enterprise-wide consumption.
- Guide the creation of reusable data assets, including data models, feature stores, machine learning pipelines, and AI‑driven solutions that enhance operational efficiency and customer experience.
- Collaborate closely with engineering, product, security, and business stakeholders to define use cases, prioritize demand, and deliver measurable business value.
- Drive adoption of modern data engineering and ML Ops practices, ensuring strong governance, data quality, and operational excellence across all data domains.
- Establish scalable standards for metadata management, observability, access controls, and data lifecycle processes.
- Apply deep expertise across streaming, warehousing, orchestration, modeling, and data quality technologies to support enterprise data needs.
- Utilize visualization platforms such as Power BI, Tableau, or Looker to enable self‑service analytics and empower business users.
Other Functions
- Operate effectively in a fast‑paced environment, balancing innovation with the rigor required to maintain data accuracy, reliability, and security.
- Lead and develop high‑performing data teams, fostering a culture of accountability, continuous improvement, and strong execution.
- Drive organizational transformation by implementing scalable AI platforms and responsible AI frameworks.
- Translate executive vision into actionable strategies and roadmaps that deliver consistent, high‑quality outcomes.
- Promote operational discipline while enabling rapid experimentation and innovation across data and AI initiatives.
Qualifications
- 10+ years of progressive IT leadership experience, including 5+ years in Data and AI at the director level or above.
- Bachelor’s degree in information technology, Computer Science, or related field (advanced degree preferred or equivalent experience).
- Airline industry experience is a plus but not required.
Knowledge, Skills and Abilities
We are looking for a visionary yet hands-on leader who can elevate our data maturity, unlock new insights through AI, and build a modern data foundation capable of supporting the company’s growth for years to come.
Equipment Operated
Standard office equipment, including PC, copier, fax machine, printer
Work Environment
Typical office environment, adequately heated and cooled
Physical Effort
Generally, not required.
Supervision Received
Consultant to Management: The incumbent exercises wide latitude in determining objectives and approaches to critical assignments.
Positions Supervised
Manager, DAI
- This role requires relocation to Denver, Colorado, where you will work closely with executive leadership and cross-functional partners.
Salary Range -$179,353-$250,000 DOE - Please note, this posting will close on or before 2/9/2026.
Workplace Policies
*Disclaimer: The above statements are intended only to describe the general nature and level of work required of the referenced position; they are not intended to be an exhaustive list of all responsibilities, duties, and skills required of individuals in this position. Please be advised that duties and expectations of this position may be subject to change.*
*Frontier Airlines, Inc. is an equal opportunity employer and, as such, is committed to providing equal employment opportunities to all qualified applicants without regard to race, color, religion, sex, national origin, age, marital status, veteran status, sexual orientation, gender identity or expression, disability status, pregnancy, genetic information, citizenship status or any other basis protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.*
*Frontier Airlines is a Zero Tolerance Drug-Free Workplace. All prospective DOT safety-sensitive employees are subject to pre-employment testing for the following drugs and their metabolites: Marijuana, Cocaine, Amphetamines, Opioids and Phencyclidine (PCP). Further, any DOT safety-sensitive job applicant who is found to have tested positive on any required drug or alcohol test at a former employer will be considered ineligible for employment with Frontier.*
*Colorado Residents: In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.*
Salary Context
This $179K-$250K range is above the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Frontier Airlines, 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 $154,000 based on 8,743 positions with disclosed compensation. Director-level AI roles across all categories have a median of $230,600. This role's midpoint ($214K) sits 39% above the category median. Disclosed range: $179K to $250K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Frontier Airlines AI Hiring
Frontier Airlines has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Denver, CO, US. Compensation range: $250K - $250K.
Location Context
AI roles in Denver pay a median of $182,000 across 122 tracked positions. That's 4% below the national 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $145,600. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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.
Frequently Asked Questions
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