Interested in this AI Product Manager role at 84.51°?
Apply Now →Skills & Technologies
About This Role
84\.51° Overview:
84\.51° is a retail data science, insights and media company. We help The Kroger Co., consumer packaged goods companies, agencies, publishers and affiliates create more personalized and valuable experiences for shoppers across the path to purchase.
Powered by cutting\-edge science, we utilize first\-party retail data from more than 62 million U.S. households sourced through the Kroger Plus loyalty card program to fuel a more customer\-centric journey using 84\.51° Insights, 84\.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.
*84\.51° follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.*
Join us at 84\.51°!
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
The AI Enablement Interaction team designs and operates a unified interaction layer between users and our AI Enablement program—helping people across 84\.51° and Kroger intuitively discover, understand, and apply AI capabilities in the tools and workflows they already use. We build and evolve the two\-way system that connects users to AI guidance while generating the signals our product teams need to continuously improve adoption, prioritization, and value realization.
As the LEAD PRODUCT MANAGER for AI Enablement Interaction, you'll own the product roadmap for our user\-facing interaction layer—including our web\-based AI knowledge hub and the broader ecosystem of experiences that connect users to AI capabilities. You'll serve as an AI subject matter expert for the program, translating complex technical strategy into intuitive, accessible user experiences. This role sits at the intersection of product management, AI fluency, and stakeholder navigation, and requires someone who is as comfortable discussing RAG pipelines and agent frameworks as they are building a product roadmap or presenting to senior leadership.
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United Stated and with the Kroger Family of Companies (i.e. H1\-B visa, F\-1 visa (OPT), TN visa or any other non\-immigrant status).
RESPONSIBILITIES:
- Own and drive the product roadmap for the AI Enablement interaction layer, prioritizing enhancements and new experiences that help users discover, understand, and apply AI capabilities across the enterprise.
- Partner closely with Lead UX and a cross\-functional design team to deliver cohesive, user\-first experiences across all interaction touchpoints—ensuring consistency, intuitiveness, and quality across the program.
- Serve as an AI subject matter expert for the program—fielding and directing a wide variety of AI\-related questions, providing high\-level support, and translating technical AI concepts (e.g. agents, RAG, fine\-tuning, Claude Code) into clear, actionable guidance for users and stakeholders.
- Act as content thought leader for the program, shaping how AI guidance, standards, and capabilities are communicated and experienced across the organization.
- Funnel AI Enablement leadership needs into the right interaction surfaces—whether that's a Hub experience, storytelling assets, release communications, or other formats—ensuring consistent and high\-quality program representation.
- Leverage user engagement analytics, feedback, and usage signals to inform product decisions and continuously optimize the interaction layer to better meet user needs and deliver measurable outcomes.
- Build strong relationships with leadership and key stakeholders across a complex organizational landscape, communicating product vision, progress, and priorities while gathering input to inform strategic decisions.
- Outline clear product requirements and acceptance criteria, partnering with cross\-functional technical leads to translate the roadmap into effective sprint and cycle plans ready for development and delivery.
- Proactively identify, manage, and communicate dependencies and risks across teams and initiatives, developing mitigation strategies to protect roadmap delivery.
- Develop and lead an AI Community of Practice, re\-imagining how users across the enterprise engage with, share, and learn from AI capabilities and each other.
QUALIFICATIONS, SKILLS, AND EXPERIENCE:
- Hands\-on experience working with AI tools and products—including practical familiarity with concepts such as agents, RAG, fine\-tuning, and tools like Claude Code and Microsoft Copilot; ability to apply this knowledge to inform product and experience decisions
- Professional experience in product management, including roadmap ownership, backlog prioritization, and end\-to\-end product lifecycle management
- Skilled in navigating complex, multi\-stakeholder environments and building relationships that influence and drive change at all levels of an organization
- Skilled in managing cross\-functional teams—including UX designers and software engineers—in an Agile environment
- Strong technical acumen; able to converse fluently with data scientists, engineers, and architects and translate complex technical concepts for non\-technical audiences
- Analytical mindset with experience using engagement analytics, user feedback, and performance metrics to drive product decisions
- Exceptional verbal and written communication skills, including the ability to develop compelling storytelling and content strategies
- Comfort with ambiguity—remains confident, resourceful, and positive when navigating evolving priorities and unexpected outcomes
- Problem solving, critical thinking, and strong planning and organizational skills
- 4–6 years of relevant experience
- Bachelor's degree or equivalent experience
\#LI\-EB1
Salary Context
This $125K-$207K range is below the median for AI Product Manager roles in our dataset (median: $188K across 140 roles with salary data).
View full AI Product Manager salary data →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 84.51°, 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. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($166K) sits 23% below the category median. Disclosed range: $125K to $207K.
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.
84.51° AI Hiring
84.51° has 5 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Positions span Cincinnati, OH, US, Chicago, IL, US. Compensation range: $207K - $207K.
Location Context
AI roles in Chicago pay a median of $205,100 across 97 tracked positions. That's 6% below the national 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.