Interested in this AI Product Manager role at New Relic?
Apply Now →About This Role
We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI\-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us!
Your opportunity
Every company shipping AI right now has the same problem: they can't see what their AI is actually doing in production. New Relic is building the answer, AI Observability, and it's one of the company's top strategic initiatives. We're running it like a startup inside the company: small teams, fast iteration, direct executive sponsorship, and a mandate to ship. As the Principal Product Manager and business owner of this initiative, you'll take it from vision through GA, then keep pushing past GA, where most of the real work actually happens, working directly with some of the largest AI deployments in the world.
What you'll do
- Own the AI Observability roadmap and the business outcomes leadership tracks (adoption, retention, expansion), plus the parts of the job that aren't purely product: pricing conversations, exec reporting, and cross\-functional escalations.
- Drive multiple engineering and design teams in parallel toward a coherent product vision, without formal authority over them.
- Partner directly with strategic enterprise customers, including their platform and infra teams deciding how to operationalize AI safely, and turn what breaks at their scale into product requirements fast enough to matter.
- Build working prototypes yourself using agentic AI workflows, so ideas get pressure\-tested before engineering time is committed to them.
- Represent AI Observability in executive strategy and prioritization decisions, and make the tradeoff calls when priorities conflict.
- Ship to GA, then keep iterating: pricing, packaging, and the next wave of features GA customers ask for once they're live.
This role requires
- 8\+ years of product management experience, including ownership of a product area from early vision through GA and post\-GA growth.
- Experience operating as a senior individual contributor who drives outcomes across teams without formal management authority.
- Demonstrated experience partnering directly with enterprise customers on production AI or LLM systems: tracing, evaluation, governance, cost, or failure modes at scale.
- Regular, current use of multiple concurrent AI agents in your own work, run asynchronously and backed by a verification process you trust instead of manual line\-by\-line review.
- Experience representing a product area in executive\-level strategy and prioritization discussions.
- We're not asking whether you use AI tools. We're asking how far along you are, and we mean it as a hard line, not a preference. This shows up across the whole job, not just code: specs, prototypes, evaluation, research, even parts of go\-to\-market. Work that used to take a team weeks should now happen in the background while you're on the next thing, and your backlog should show it.
Bonus points if you have
- Prior experience in observability, APM, security, or developer tools.
- Experience sitting in customer escalations at the VP or CTO level.
- A public track record (writing, talks, open source) of how you personally use agentic AI workflows.
- You've built or shaped the verification and review systems your team trusts to run AI agents at scale, not just operated inside systems someone else built.
Please note that visa sponsorship is not available for this position.
\#LI\-GK1 \#LI\-*Remote*
The pay range below represents a reasonable estimate of the salary for the listed position. This role is eligible for a corporate bonus plan. Pay within this range varies by work location and may also depend on job\-related factors such as an applicant’s skills, qualifications, and experience.
New Relic provides a variety of benefits for this role, including healthcare, dental, vision, parental leave and planning, and mental health benefits, a 401(k) plan and match, flex time\-off, 11 paid holidays, volunteer time\-off, and other competitive benefits designed to improve the lives of our employees.
Estimated Base Pay Range
$193,000 \- $241,000 USD
Fostering a diverse, welcoming and inclusive environment is important to us. We work hard to make everyone feel comfortable bringing their best, most authentic selves to work every day. We celebrate our talented Relics’ different backgrounds and abilities, and recognize the different paths they took to reach us – including nontraditional ones. Their experiences and perspectives inspire us to make our products and company the best they can be. We’re looking for people who feel connected to our mission and values, not just candidates who check off all the boxes.
If you require a reasonable accommodation to complete any part of the application or recruiting process, please reach out to [email protected].
We believe in empowering all Relics to achieve professional and business success through a flexible workforce model. This model allows us to work in a variety of workplaces that best support our success, including fully office\-based, fully remote, or hybrid.
Our hiring process
In compliance with applicable law, all persons hired will be required to verify identity and eligibility to work and to complete employment eligibility verification. Note: Our stewardship of the data of thousands of customers means that a criminal background check is required to join New Relic.
We will consider qualified applicants with arrest and conviction records based on individual circumstances and in accordance with applicable law including, but not limited to, the San Francisco Fair Chance Ordinance.
Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. New Relic does not accept unsolicited headhunter and agency resumes, and will not pay fees to any third\-party agency or company that does not have a signed agreement with New Relic.
New Relic develops and distributes encryption software and technology that complies with U.S. export controls and licensing requirements. Certain New Relic roles require candidates to pass an export compliance assessment as a condition of employment in any global location. If relevant, we will provide more information later in the application process.
Candidates are evaluated based on qualifications, regardless of race, religion, ethnicity, national origin, sex, sexual orientation, gender expression or identity, age, disability, neurodiversity, veteran or marital status, political viewpoint, or other legally protected characteristics.
Review our Applicant Privacy Notice at https://newrelic.com/termsandconditions/applicant\-privacy\-policy
Salary Context
This $193K-$241K range is above the median for AI Product Manager roles in our dataset (median: $185K across 167 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 4,317 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At New Relic, 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 in Demand for This Role
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 $217,100 based on 471 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. Disclosed range: $193K to $241K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
New Relic AI Hiring
New Relic has 1 open AI role right now. They're hiring across AI Product Manager. Based in Atlanta, GA, US. Compensation range: $241K - $241K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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