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About This Role
About Delinea:
Delinea is a pioneer in securing human and machine identities through intelligent, centralized authorization, empowering organizations to seamlessly govern their interactions across the modern enterprise. Leveraging AI\-powered intelligence, Delinea’s leading cloud\-native Identity Security Platform applies context throughout the entire identity lifecycle – across cloud and traditional infrastructure, data, SaaS applications, and AI. It is the only platform that enables you to discover all identities – including workforce, IT administrator, developers, and machines – assign appropriate access levels, detect irregularities, and respond to threats in real\-time. With deployment in weeks, not months, 90% fewer resources to manage than the nearest competitor, and a 99\.995% uptime, Delinea delivers robust security and operational efficiency without compromise. Learn more about Delinea on Delinea.com, LinkedIn, X, and YouTube.
Join our passionate, global team at Delinea and help us make the world a safer and more secure place. Our success is driven by world\-class product leadership, outstanding engineers, and strategic investment from TPG. We value diversity, innovation, and a culture of respect and fairness. If you're ready to push boundaries and challenge the status quo in security, we want to hear from you.
Apply today to help us achieve our mission.
About the Iris AI Team:
Iris AI is the team building the AI\-powered capabilities of the Delinea Platform. We put LLMs to work on real security problems: detecting anomalies in audit data, making authorization decisions smarter, and building agents that do real work for our customers. The problems are new, the pace is fast, and what you build ships to some of the world's largest organizations.
Summary:
You'll design, build, and run the cloud services behind Delinea's AI features, with LLMs as part of your toolkit: inference, retrieval, agents, and evaluation are all product surface you own. Our services are written in C\#/.NET, Python, and Go. Be strong in one, and be willing to work in any. You'll report to the Director of Engineering, Iris AI.
What You'll Do
- Build and run scalable, highly available backend services in C\#/.NET, Python, and Go on Azure and Kubernetes.
- Build LLM\-powered features on platforms like Azure AI Foundry: model integration, context pipelines, RAG, tool calling, agents, and evals.
- Design event\-driven, asynchronous architectures across our microservices.
- Own delivery end to end: Terraform, CI/CD, monitoring, and production incident response.
- Work closely with product, UX, and other platform teams; give and get sharp code and design reviews.
- Build with AI every day. We use coding agents to design, write, and review code, and we hold that code to the same bar as anything written by hand.
What You'll Need:
- A degree in Computer Science or a related field, or equivalent experience.
- 8\+ years designing and building production backend services in C\#/.NET, Python, or Go, with experience across the full software development lifecycle.
- Hands\-on experience building products with LLMs (not just using them): inference, structured outputs, RAG, tool calling, or agents on Azure AI Foundry, the OpenAI API, Amazon Bedrock, Google Vertex AI, the Anthropic API, or similar.
- Fluency with AI\-assisted development (Claude Code, GitHub Copilot, Cursor) treated as a discipline in its own right: spec\-driven development, careful context, and verified, tested output.
- Strong grasp of distributed systems, API design, and microservices, plus experience with a major cloud provider.
- Solid understanding of multi\-tenant SaaS architecture and the trade\-offs of operating at scale.
We'd Love to See:
- Experience building tools, APIs, or integrations that AI agents call \- MCP servers, function/tool\-calling interfaces, plugins, or similar.
- ML and MLOps depth: fine\-tuning, eval harnesses, and deploying and evaluating models in production.
- Kubernetes, Terraform, and CI/CD pipelines.
- Identity security, PAM, or Zero Trust background.
For this Job, Delinea is not considering candidates that need any type of US work authorization now or in the future. This includes, but is not limited to: F1\-OPT, F1\-CPT, H\-1B, TN, L\-1, J1, etc.
Why work at Delinea?
- We're passionate problem\-solvers helping the world's largest organizations protect what matters most: their human and machine identities.
- We invest in people who are smart, self\-motivated, and collaborative.
- What we offer in return is meaningful work, a culture of innovation and great career progression.
At Delinea, our core values are STRONG and guide our behaviors and success:
- Spirited \- We bring energy and passion to everything we do
- Trust \- We act with integrity and deliver on our commitments
- Respect \- We listen, value different perspectives, and work as one team
- Ownership \- We take initiative and follow through
- Nimble \- We adapt quickly in a fast\-changing environment
- Global \- We embrace diverse people and ideas to drive better outcomes
We believe weaving these core values into our day\-to\-day actions, and our process for hiring, evaluating, and promoting employees, helps us cultivate a work environment that embraces collaboration and camaraderie.
We take care of our employees. We offer competitive salaries, a meaningful bonus program, and excellent benefits, including healthcare insurance, as well as pension/retirement matching, comprehensive life insurance, an employee assistance program, time off plans, and paid company holidays.
*Delinea is an Equal Opportunity and Affirmative Action employer and prohibits discrimination and harassment of any type with regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.*
*Upon conditional offer of employment, candidates are required to complete comprehensive criminal background check, verification of education, and verification of employment, per employment policy. In addition, all publicly posted social media sites may be reviewed.*
Compensation Range: $130K \- $162\.2K
Salary Context
This $130K-$162K range is in the lower quartile 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 Delinea, 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 $217,100 based on 471 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($146K) sits 33% below the category median. Disclosed range: $130K to $162K.
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.
Delinea AI Hiring
Delinea has 2 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Based in Redwood City, CA, US. Compensation range: $150K - $162K.
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.
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