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About This Role
### Who We Are
At Apptegy, we are more than a tech company; we are partners dedicated to transforming how schools communicate and shape the future of education. Your work here will directly empower districts to share their stories, engage their communities, and celebrate student success. We're a team of thoughtful, high\-performing individuals committed to making a tangible impact. If you're looking for a dynamic environment where you'll be supported with exceptional mentorship and resources to grow your career, come build with us.The Role
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As Senior Product Manager, Internal AI \& Automation, you will own the product layer of Apptegy's internal AI function. You will work directly with leaders and teams across Sales, Customer Success, Marketing, Finance, People, and other parts of the business to identify high\-value workflows where AI can materially improve how work gets done.
You will turn those opportunities into a focused roadmap, build and test the first working versions directly, and partner with our AI Ops Engineer to make the solutions reliable and scalable. You will own the product decisions, success metrics, rollout plans, and adoption of the tools you launch.
This is a senior individual contributor role on a lean, high\-visibility team. You will be expected to move from ambiguity to action without waiting for a fully defined roadmap, make clear tradeoffs about where to focus, and stay close to the details of the workflows and tools you are changing. You will partner with the VP of Product and Chief Product and Technology Officer to translate company priorities into a practical portfolio of internal AI products, then help shape how this function grows over time.
Why You'll Love This Job
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As Senior Product Manager, Internal AI \& Automation at Apptegy, you'll get to build, really build. You'll move from insight to a working V1, then partner with a dedicated AI Ops Engineer to turn what works into something the organization can rely on.
This is a new function with direct visibility to the VP of Product and Chief Product and Technology Officer. You will have meaningful ownership over what this team becomes, which workflows it takes on, and how Apptegy approaches internal AI over time.
Your work will be visible and measurable. You will work directly with Sales, Customer Success, Marketing, Finance, People, and other business teams, then see the tools you launch change how those teams work. You will not be managing a large portfolio or waiting for a fully defined roadmap. You will have the space to make clear choices, move quickly, and stay close to the problem, the users, and the outcome.
This is an opportunity to shape a practical internal AI function from the ground up, with enough support to scale what works and enough autonomy to define the path forward.
What You'll Do
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- Run rapid discovery across operational teams to identify high\-value, repeatable workflows where AI can drive step\-change improvements — not just incremental automation, but fundamentally different ways of working.
- Own V1 end\-to\-end: use LLM APIs, no\-code, and low\-code tools to get to a working prototype fast, validate it with real users, and prove out the value before investing in scale.
- Partner with your AI Ops Engineer to systematize what works — turning scrappy V1s into production\-grade tools that are reliable, maintainable, and built to last.
- Treat internal teams as your clients — understand how they actually work, find the real friction, and build tools that earn a permanent place in their daily workflow.
- Redesign workflows from first principles — if AI handles the repetitive work, what does this role actually look like?
- Ship rollout plans and usage playbooks alongside every tool you launch, so adoption isn't left to chance.
- Define success metrics for every tool you ship and own adoption within the teams using them.
- Maintain a visible backlog of automation opportunities, sequenced by business impact, and communicate priorities clearly to leadership.
- Stay current on the rapidly evolving AI and automation landscape and surface relevant tools, models, and patterns that could accelerate the work.
Who You Are
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- 5\-10 years of product management experience. Your résumé is full of things you built, not just things you planned.
- You are a systems thinker. You understand the people an agent serves and how their work actually flows: where decisions happen, where context gets lost, and where things slow down. You assume the requests and complaints you receive are incomplete, and you look for the need that is actually worth solving.
- You are hands on with agents. You do not just write requirements and hand them off. You work directly with prompts, documents, tools, and delegation, prototype against real runs, and partner with engineering on harder capabilities.
- You have strong intuition for LLMs: how they are prompted, how they delegate to one another, and how they are evaluated. You know what makes an agent accurate, reliable, on tone, and trusted, and you stay current on what is newly possible.
- You thrive in ambiguity. When the problem is half defined and the path is not clear, you start, learn, and adjust without waiting for perfect conditions.
- You have built AI tools, automation workflows, or internal tools before. You know what zero to working looks like and have done it without waiting for a fully staffed engineering team.
- You are technically fluent enough to build V1s independently, comfortable with LLM APIs, agent frameworks, and workflow automation tools, and collaborative enough to hand off cleanly when it is time to systematize.
- You have strong cross functional instincts. You build credibility quickly with different kinds of stakeholders, get into the details of how teams work, and translate what you find into something buildable.
- You have a track record of driving measurable outcomes, not just shipping features.
What Makes You Stand Out
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- You've worked closely with business teams and understand how operational workflows actually run day\-to\-day — not just what's in the process doc, but what's really happening.
- Experience deploying AI agents in an operational context — tools like Gong, Intercom, Salesforce, or Glean have been part of your work.
- Comfort working with the modern AI and automation stack: Claude or OpenAI APIs, n8n for workflow orchestration, Glean or Snowflake for data access, and the ability to stitch them together into something a real team will actually use.
- You've redesigned a human workflow around AI — not bolted AI onto an existing process, but genuinely rethought how the work gets done.
- Familiarity with B2B SaaS operations and the levers that drive efficiency at scale.
The base salary range for this role is $140,000–$210,000 per year. This is the expected compensation band for the position, not a guaranteed offer. Final compensation will be based on relevant experience, skills, scope of impact, internal equity, and business needs. The range reflects base salary only.
### Why Apptegy
Join a team that's committed to your success. At Apptegy, we're passionate about creating an environment where you can do your best work and find true fulfillment. We believe in investing in our people—both professionally and personally—because your well\-being drives our collective impact.
US Employee Benefits:
Comprehensive medical, dental, vision, and life insurance coverage
Retirement 401(k) with employer match
Health Savings Accounts (HSA) and Flexible Spending Accounts (FSAs)
Mental Health Reimbursement
Unlimited paid time off, including seasonal (December) company\-wide time off
Paid parental and medical leave
MX Employee Benefits:
Private medical insurance for you and your dependents
Life insurance
15 days Aguinaldo
Vales de Despensa
Fondo de Ahorro
Caja de Ahorro
Flexible paid time off policy
Paid travel to/from Little Rock, Arkansas for Onboarding.
Apptegy champions the thoughtful integration of AI to empower our teams and processes. As we seek to understand your individual capabilities and how you might contribute, we ask that all responses to application questions and during interviews are genuinely your own. Please refrain from using AI generation tools, as our aim is to assess your authentic voice and expertise.
Equal Opportunity Employer
Apptegy is an equal\-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, protected veteran or disabled status, or genetic information.
Salary Context
This $140K-$210K range is below 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 Apptegy, 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 ($175K) sits 19% below the category median. Disclosed range: $140K to $210K.
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.
Apptegy AI Hiring
Apptegy has 1 open AI role right now. They're hiring across AI Product Manager. Based in New York, NY, US. Compensation range: $210K - $210K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
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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