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About This Role
Robots & Pencils is an applied AI engineering firm building the next frontier of business architecture. We design and ship AI co-workers that integrate into enterprise operations and deliver measurable results for our clients. We're all in on AWS, combining deep UX capability with senior engineering talent to get AI into production fast and keep it there.
We've earned the trust of leaders across Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, and Manufacturing and more, and earned a reputation as the nimble alternative to traditional global systems integrators. Founded in 2009, with delivery centers in Canada, the United States, Eastern Europe, and Latin America, we are smaller, faster, and more senior by design. Our teams average 15+ years of experience. We move fast, sweat the details, and build things that actually ship.
Position Overview
We're looking for a Senior Product Manager, AI to lead end-to-end product delivery for complex GenAI and agentic AI engagements. This role demands deep AI fluency, hands-on prototyping ability, and the product judgment to navigate non-deterministic systems at enterprise scale. It is ideal for an experienced AI product leader who can own the full arc of an engagement — from framing the problem through shipping a production-grade agentic solution — while building trusted relationships with senior client stakeholders.
In this role, you will work as the primary product lead on a cross-functional AI delivery team, owning the roadmap, defining agent behavior, running evals, and guiding delivery from discovery through phased rollout. You'll bring the technical depth to engage meaningfully with engineering on architecture decisions and the communication skills to frame AI tradeoffs clearly for executive audiences.
Why This Role Matters
At Robots & Pencils, we design AI systems for a human world. Our name says it all. Robots and pencils means engineering paired with creativity, because every agent we ship has to work for real people in real workflows. That balance is baked into how we operate.
Every role here contributes directly to that mission. Here, you shape how AI systems integrate into enterprise operations, how teams move at real velocity, and how products create measurable impact for clients and the people they serve. We ship production-ready AI in 30 to 45 days. That pace demands people who take ownership, lead with craft, and care deeply about what they put their name on.
What You'll Do
Craft & Delivery
- Own end-to-end product delivery for complex AI and agentic AI engagements, from discovery and hypothesis framing through phased rollout and production readiness
- Define and maintain AI product roadmaps that connect agent capabilities to measurable enterprise business outcomes
- Lead discovery activities including user research, stakeholder interviews, and assumption testing — framing the riskiest hypotheses first and de-risking them before committing to build
- Design and run experiments including POCs, pilot deployments, and scenario-based testing of multi-step agentic workflows, edge cases, and failure recovery
- Define agent behavior end-to-end including system prompts, tool schemas, context management, summarization, and working memory patterns across multi-step tasks
- Own and run evals frameworks covering task completion, reasoning quality, tool selection, failure recovery, and safety — iterating based on evidence rather than assumptions
- Define success metrics at the agent level including task completion rate, cost per task, escalation rate, and time to resolution alongside business KPIs
- Establish human-in-the-loop boundaries and guardrails — when the agent acts autonomously, when it escalates, and how to handle non-deterministic output
- Bring an AI-forward mindset to your daily work, using tools like Claude, Claude Code, Cursor, and GitHub Copilot — and agentic frameworks where relevant — to move faster than traditional product
Collaboration & Communication
- Lead stakeholder working sessions, prioritization discussions, and risk conversations with senior client stakeholders with confidence and clarity
- Communicate complex AI tradeoffs, agent behavior, and product decisions clearly to both technical and non-technical executive audiences
- Build trusted relationships with client stakeholders and serve as a reliable, consultative partner throughout the engagement
Leadership & Influence
- Lead prioritization decisions by balancing business value, technical feasibility, cost, latency, and delivery timelines
- Frame every request in terms of user and business outcomes, pushing back on feature-level thinking and managing AI hype cycles with realistic expectations
- Begin mentoring junior AI PMs on the engagement, sharing knowledge on evals, agent design, and AI product delivery practices
What You'll Bring
- 5+ years of experience in product management with hands-on experience shipping AI features or products
- Ability to read code (Python, JavaScript, or TypeScript), evaluate architecture decisions, and make informed product tradeoffs on technical constraints
- Deep understanding of AI concepts including LLMs, RAG, fine-tuning, prompt and context engineering, agentic systems such as planning, tool use, human-in-the-loop controls, and guardrails, and evals
- Proven ability to prototype AI and agentic solutions using modern AI tools to validate hypotheses and de-risk product decisions (e.g., Claude, Claude Code, Cursor, GitHub Copilot)
- Experience running evals for AI systems and iterating based on results
- Experience defining agent behavior including system prompts, tool schemas, and human-in-the-loop boundaries
- Strong experience working with AWS AI services in a product context (e.g., Bedrock, Lambda, SageMaker, Kendra)
- Strong client communication skills and the ability to frame AI capabilities and limitations for non-technical executive audiences
- Comfortable operating in ambiguous, fast-moving environments where the AI landscape evolves rapidly
- Experience in a consulting or agency environment, familiarity with agent orchestration frameworks (LangChain, LangGraph, AWS Strands), or a software engineering background (Python, JavaScript, TypeScript) is a plus
Helpful Extras and Unique Skills
You'll Do Well Here if You Are
- A doer. You see something broken and fix it. You'd rather move on clarity than wait for certainty.
- A fast learner who knows you don't know everything. The AI landscape changes weekly. You're senior enough to know better and curious enough to keep learning anyway.
- Direct in a way that makes the work better. You give honest feedback. You'd rather have the hard conversation than blow smoke.
- Obsessed with craft. You know genius is in the details. You ship exceptional, not perfect, and you don't put your name on work you wouldn't stand behind.
- Built for ownership. You honor commitments, admit mistakes fast, and back your teammates when a decision costs something. No handoffs, no finger-pointing.
- All in. You treat clients' businesses like your own. You take the work seriously without taking yourself seriously.
- Resourceful when the budget, timeline, or team is tight. Constraints don't slow you down. They sharpen you.
- Glad to be in the room with people who care as much as you do. Our teams average fifteen-plus years of experience. We hire people who push each other to do better work.
The below range reflects the range of possible compensation for this role at the time of this posting. We may ultimately pay more or less than the posted range. This range may be modified in the future. An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, shift, travel requirements, sales or revenue-based metrics, any collective bargaining agreements, and business or organizational needs. The salary range for this role is $130.000 USD - $165.000 USD. We offer a comprehensive package of benefits including paid time off, medical/dental/vision insurance and 401(k) to eligible employees.
An offer of employment may be conditional upon successful completion of a background check in accordance with local legislation and our candidate privacy notice. Your current employer will not be contacted without your permission. We are committed to ensuring equal employment opportunities for all job applicants and employees. Employment decisions are based upon job-related reasons regardless of an applicant's race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, marital status, genetic information, protected veteran status, or any other status protected by law.
Salary Context
This $270K-$343K range is above the 75th percentile for AI Product Manager roles in our dataset (median: $194K across 123 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 9,079 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Robots & Pencils, 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 $220,200 based on 947 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($306K) sits 39% above the category median. Disclosed range: $270K to $343K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Robots & Pencils AI Hiring
Robots & Pencils has 3 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Positions span Orange County, CA, Philadelphia, PA, US. Compensation range: $343K - $343K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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