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About This Role
United States, Georgia, Atlanta
Reservations \& Cust. Care
14\-Jul\-2026
Ref \#: 33234
### How you'll help us Keep Climbing (overview \& key responsibilities)
Now is an exciting time to be part of Experience Design \& Technology team in Delta’s Reservations and Care department as we redefine customer and employee experiences by setting new technology standards. Our team is looking for a product manager to drive the vision of AI and automation products as well as deliver better customer and employee experiences in our Customer Engagement Centers.
Summary of Responsibilities (not comprehensive):
- Strategically identify opportunities to increase customer and specialist satisfaction and build into executable product roadmap.
- Own the end\-to\-end delivery for AI products, defining OKRs, and using data to continuously optimize customer experience, specialist effectiveness, adoption, and business value.
- Proactively identify optimization opportunities across AI and automation products, collaborating with cross\-functional stakeholders to prioritize, test, and implement improvements that enhance customer experience and operational efficiency.
- Develop business cases and ROI models to support investment decisions for AI and automation.
- Deliver high\-impact executive communications to Reservations leadership to influence funding decisions for strategic initiatives.
- Manage cross\-functional collaboration with frontline specialists, field leaders, and technical teams to drive AI adoption and operational excellence.
- Play an integral role in engagement, communication, change management, feedback loops, and overall leadership visibility across the system.
- Embrace diverse people, thinking, and styles.
- Develop both strategic and tactical plans that create a safety\-conscious environment resulting in employee safety and wellbeing.
### Benefits and Perks to Help You Keep Climbing
Our culture is rooted in a shared dedication to living our values – Care, Integrity, Resilience and Servant Leadership – every day, in everything we do. At Delta, our people are our success. At the heart of what we offer is our focus on Sharing Success with Delta employees. Exploring a career at Delta gives you a chance to see the world while earning great compensation and benefits to help you keep climbing along the way:
- Competitive salary, industry\-leading profit sharing program, and performance incentives
- 401(k) with generous company contributions up to 9%
- New hires are eligible for up to 2\-weeks of vacation. This is earned for use in the following vacation year (April 1 – March 31\)
- In addition to vacation, new hires are eligible for up to 56 hours of paid personal time within a 12\-month period
- 10 paid holidays per calendar year
- Birthing parents are eligible for 12\-weeks of paid maternity/parental leave
- Non\-birthing parents are eligible for 2\-weeks of paid parental leave
- Comprehensive health benefits including medical, dental, vision, short/long term disability and life insurance benefits
- Family care assistance through fertility support, surrogacy and adoption assistance, lactation support, subsidized back\-up care, and programs that help with loved ones in all stages
- Holistic Wellbeing programs to support physical, emotional, social, and financial health, including access to an employee assistance program offering support for you and anyone in your household, free financial coaching, and extensive resources supporting mental health
- Domestic and International space\-available flight privileges for employees and eligible family members
- Career development programs to achieve your long\-term career goals
- World\-wide partnerships to engage in community service and innovative goals created to focus on sustainability and reducing our carbon footprint
- Business Resource Groups created to connect employees with common interests to promote inclusion, provide perspective and help implement strategies
- Recognition rewards and awards through the platform Unstoppable Together
- Access to over 500 discounts, specialty savings and voluntary benefits through Deltaperks such as car and hotel rentals and auto, home, and pet insurance, legal services, and childcare
### What you need to succeed (minimum qualifications)
- Experienced Product Owner with a strong track record of delivering impactful AI solutions
- Strategic thinking and creative problem\-solving skills with ability to translate data into a logical and actionable story.
- Demonstrated initiative and ability to manage multiple priorities.
- Curious mindset, willing to ask “why” until root causes of use cases are identified.
- Proficiency in written and oral communications and able to produce concise, relevant, documents and presentations.
- Must be performing satisfactorily in present position.
- Consistently prioritizes safety and security of self, others, and personal data.
- Embraces diverse people, thinking, and styles.
- Possesses a high school diploma, GED, or high school equivalency.
- Is at least 18 years of age and has authorization to work in the United States.
### What will give you a competitive edge (preferred qualifications)
- Experience with Agile methodologies, VersionOne, Jira, or similar product management tools.
- Advanced proficiency using analytics and visualization tools to drive product decisions and communicate insights.
- Working knowledge of SQL, Excel, Power BI, Tableau, or similar analytical platforms.
- Experience defining and tracking product OKRs, KPIs, and value realization metrics.
- Experience with AI, machine learning, automation, or conversational AI products.
- Experience applying experimentation frameworks, hypothesis testing, and data\-driven product optimization.
Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 3,708 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Delta Air Lines, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $216,175 based on 270 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Delta Air Lines AI Hiring
Delta Air Lines has 1 open AI role right now. They're hiring across AI Product Manager. Based in Atlanta, GA, US.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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