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About This Role
At Jamf, we believe in an open, flexible culture based on respect and trust. Our track record and thriving work environment all stem from the freedom we grant ourselves to get the job done right. We take pride in helping tens of thousands of customers around the globe succeed with Apple.
The secret to our success lies in our connectivity, while operating with a high degree of flexibility. Work\-life balance remains our priority while feeling connected is important to maintain our strong culture, achieve our goals, and thrive as \#OneJamf.
What you'll do at Jamf:
The Senior Software Engineer is responsible for building the tools required to help organizations succeed with Apple. Lead others on the agile team to break down problems and apply the appropriate designs and practices to build Jamf products.
Subject matter expert in various Jamf components and product offerings. Mentor and coach others while delivering new components and features with high quality and reliability.
You may be required to work periodically at a Jamf office or collaborative work location with other Jamf employees in your area for certain events or moments that matter.
What you can expect to do in this role:
- Break down customer problems into work you and the team can execute on.
- Independently complete tasks from start to finish with high quality.
- Ability to communicate technical concepts to stakeholders.
- Use your knowledge of Engineering best practices to ask the right questions, solve problems and build great software with a high level of quality.
- Produce designs for new and existing features.
- Clearly communicate technical concepts with others in the organization (Technical Communication, Support, Product and Cloud).
- Performs all job responsibilities in alignment with the core values, mission and purpose of the organization.
- Adheres to the highest moral, ethical and legal standards to deliver and environment that promotes respect, innovation and creativity.
- Supports and promotes a positive, inclusive workplace one in which the talents and strengths of our increasingly diverse workforce are welcomed, further developed and manifested in our work.
- Build and operate agentic workflows that act on production systems \- a model planning and executing multi\-step work against real infrastructure, not assisting in an editor
- Design their guardrails: blast\-radius limits, rollback, CI as a mandatory gate, and confidence thresholds deciding what runs automatically versus what queues for approval
- \#LIRemote
What we are looking for:
- Minimum of 5 years of experience developing enterprise grade software with understanding of testing and quality assurance processes (Required).
- Minimum of 5 years of demonstrated experience in current programming language and tools based on position requirements (Required).
- Hands\-on experience building with LLM APIs and agentic frameworks: tool calling, multi\-step execution, structured output (Beyond AI coding assistants) (Required)
- Thinks in terms of trust boundaries, blast radius, and least privilege — including about the automation itself, which holds elevated access to production (Required)
- Understands vulnerability management as a discipline: severity and exploitability, SLAs, exception handling, and why an unpatched system with a documented exception differs from one nobody noticed (Required)
- AI coding agents at repository scale (Claude Code or equivalent) \- running them across many repos and building the harness that makes their output trustworthy (Preferred)
- Evaluation and observability for non\-deterministic systems: measuring accuracy, catching silent degradation (Preferred)
- AI governance in a security context \- model\-use policy, data handling, and the audit questions that follow an agent\-initiated production change (Preferred)
- General Experience performance and load testing applications (Preferred)
- Experience building enterprise level software
- Experience working within an agile organization
- Understanding of build systems such as Jenkins or Bamboo
- Strong communication skills
- Proven analytical and problem\-solving skills
- Ability to interact effectively with co\-workers in a results driven culture
- Ability to engage with and establish trust and rapport with all levels of customers and employees
- Solution focused ability working collaboratively in a fast\-paced environment
- Apple platform experience
- 2 year / Associates (Required)
- 4 year Bachelors Degree (Preferred)
- A combination of relevant experience and education may be considered
SECURITY AND PRIVACY REQUIREMENTS
- Participation in ongoing security training is mandatory
- Established security protocols will be adhered to, sensitive data will be handled responsibly, and data protection practices are followed, including understanding relevant privacy regulations and reporting breaches
- Acknowledging the Jamf Code of Conduct, where applicable security and privacy policies can be found, is a requirement of all roles at Jamf
How we help you reach your best potential:
- Named a 2025 Best Companies to Work For by U.S. News
- Named a 2024 Best Technology Company to Work For by U.S. News
- Named one of Forbes Most Trusted Companies in 2024
- Named a 2024 Best Companies to Work For by U.S. News
- Our developers work in agile delivery teams to produce new features, improve software components, and are the subject matter experts for our Jamf product offerings.
- You will have the opportunity to make a real and meaningful impact for more than 75,000 global customers with the best Apple device management solution in the world.
- We constantly push the boundaries of technology, our developers support new innovations and OS releases the moment they are made available by Apple.
- Several Jamf engineers are named in patents and with team names like CatDog, ThunderSnow and Dalek you can expect to have some fun while building cutting\-edge software.
- You will have the opportunity to work with a small and empowered team where the culture is based on trust, ownership, and respect.
- We offer a clear career path that enables you to grow under supportive leadership and management
- Visit our Jamf Engineering blog to learn more about the innovative projects our team is working on and what we learn from each challenge we solve. A blog written by engineers, for engineers at medium.com/jamf\-engineering
- 22 of 25 world's most valuable brands rely on Jamf to do their best work (as ranked by Forbes).
- Over 100,000 Jamf Nation users, the largest online IT community in the world.
Pay Transparency
At Jamf, base pay is one part of our total compensation package and is set within a defined range. These ranges can vary based on hiring location. Where an individual's pay falls within that range depends on several factors, including role scope, location, budget, skills, experience, and qualifications. This approach helps ensure fair, competitive pay and provides room to grow as you develop in your role.
What it means to be a Jamf?
We are a team of free\-thinkers, can\-doers, and problem\-crushers. We value humility and the relentless pursuit of knowledge. Our culture flows from a spirit of selflessness and relentless self\-improvement \- driving both personal growth and collective progress throughout our company. We unite around common goals while respecting personal approaches, believing that fulfilled individuals create a thriving, vibrant workplace.
Our aim is simple: hire exceptionally good people who are incredibly good at what they do and let them do it. We provide the support and resources to let everyone be their authentic, best selves at work, at rest, and at play. We are committed to supporting the continual improvement of Apple in the workplace, the organizations that rely on them and the people who keep it all running smoothly.
Above it all, waves our banner of \#OneJamf – and the knowledge that when we stand together, we accomplish so much more than we could alone. We seek individuals who share this unwavering journey toward growth to join us in our quest for constant improvement.
What does Jamf do?
Jamf extends the legendary Apple experience people enjoy in their personal lives to the workplace. We believe the experience of using a device at work or school should feel the same, and be as secure as, using a personal device. With Jamf, customers are able to confidently automate Mac, iPad, iPhone and Apple TV deployment, management, and security – anytime, anywhere – to protect the data and applications used by employees in the workplace, students learning in the classroom, and streamline communications in healthcare between patients and providers. More than 2,500 Jamf strong worldwide, we are free\-thinkers, can\-doers, and problems crushers who are encouraged to bring their whole selves to work each and every day.
Get social with us and follow the conversation at \#OneJamf
*Jamf is committed to creating an inclusive \& supportive work environment for all candidates and employees. Candidates with disabilities or religious beliefs are encouraged to reach out if they need additional support or alternative options to our recruiting processes to accommodate their disability or religious belief. If you need an accommodation, please contact your Recruiter or Recruiting Coordinator directly. Requests for accommodation will be handled confidentially by Recruiting and will not be shared with the hiring manager. Jamf is an equal opportunity employer and does not discriminate against individuals who request reasonable accommodation for disability or religious beliefs. To request accommodations please email us at* *[email protected]*
Salary Context
This $113K-$205K 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 jamf, 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 ($159K) sits 27% below the category median. Disclosed range: $113K to $205K.
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.
jamf AI Hiring
jamf has 1 open AI role right now. They're hiring across AI Product Manager. Based in Remote, US. Compensation range: $205K - $205K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
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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