AI Product Manager CV: Examples & Template (2025)

Writing an AI product manager CV is about showing measurable value, not just dropping buzzwords. Employers want proof you can define problems, partner with engineers and data scientists, and deliver tangible outcomes.

By following a proven AI product manager CV template and expert tips, you can highlight your achievements and stand out. This guide offers AI product manager CV examples and practical advice for creating a job application that impresses recruiters and hiring managers alike.

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Looking for a CV-writing guide for a different position? Here’s a selection for you:

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AI product manager CV example

Now, here’s how to write an AI product manager CV step by step:

1. Start your AI product manager CV with a winning personal statement

A CV personal statement (CV profile) is the equivalent of a first impression. Structure your CV introduction into 3–4 sentences (50–150 words) that: 

• Introduce who you are as a product leader (seniority, domain, sectors).
• Summarise your most relevant AI/ML achievement with numbers.
• Explain what you’ll bring to the role.
  
  

Last but not least: write the CV summary last. Once your experience and projects are clear, it will be easier to draft.

AI product manager CV example: personal statement

A strong CV summary will convince the recruiter you’re the perfect candidate. Save time and choose a ready-made personal statement written by career experts and adjust it to your needs in the LiveCareer CV builder.

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2. Showcase product experience on your AI product manager CV

The work history section is the most important part of any AI product manager's CV. Employers want to understand the scope of past roles, and, just as importantly, the results that were delivered. The best way to present this is with a reverse-chronological CV format, beginning with your current or most recent position and working backwards.

For each role, include the following details:

• Job title, e.g. AI Product Manager or Senior AI Product Manager
• Employer and location (specify if remote or hybrid)
• Dates of employment in this format: Month Year–Month Year

Under each subheading, use a short list of bullet points to cover both:

• Key responsibilities: core duties and the areas for which you were accountable, such as product roadmapping, stakeholder management, or collaborating with data scientists on model deployment.
• Key achievements: measurable results that show how you added value, such as improving feature adoption, reducing deployment times, or increasing revenue.

When writing work experience bullet points, start with action verbs and aim to combine responsibilities with outcomes where possible. For example:

• Managed the product lifecycle for three AI-driven features, from ideation to launch, resulting in a 14% increase in customer retention.
  

This approach gives recruiters the whole picture: what you were responsible for day-to-day and how effectively you carried out those responsibilities.

However, if you’re early in your AI PM career, use a different approach. Lead with high-impact projects, university research projects, or internships. Quantify the impact of all the professional accomplishments wherever possible.

AI product manager CV example: product experience

3. Don’t neglect the educational background

The education section is an integral part of an AI product manager's CV, especially if you’re applying for roles in such a technically demanding field. When listing your degrees, start with the highest credential and work backwards.

For each entry, include:

• Degree type and subject, e.g. MSc Artificial Intelligence
• Institution name and location
• Dates attended: Month Year–Month Year
• Degree classification, if relevant

If you’re still studying, mention the expected graduation date. For early-career candidates without extensive experience, the education section will carry extra weight. In this case, include relevant coursework, academic projects, or dissertations that demonstrate your ability to work with data, algorithms, or user-centred design.

AI product manager CV example: education

4. Put relevant skills on display in your AI product manager CV

The skills section is a snapshot of the expertise you’ll bring to the role, so keep it concise and targeted. When selecting which hard and soft skills to include, prioritise those most relevant to the specific job description and the company’s product focus. Review the advertisement carefully, highlighting recurring keywords, and ensure the skills you list match what the employer is seeking.

Avoid generic buzzwords like “team player” or “hard worker.” Instead, prioritise skills that show your ability to deliver AI products in practice, whether it’s working with data pipelines, running experiments, or managing stakeholders. Aim for 6–10 skills that you can confidently explain and illustrate with examples during an interview.

AI product manager CV example: skills

5. Harness the power of additional sections

Your CV doesn’t have to stop at work history and education. Adding well-chosen extra sections can help you stand out and provide employers with a more comprehensive picture of your qualifications.

Depending on your background, you may want to include some of these extra sections:

• Projects & portfolio: Showcase examples of your work with links to online portfolios, GitHub, or published pieces (share only what you own or are permitted to).
• Publications & presentations: List articles, talks, or case studies that demonstrate professional credibility.
• Certifications & training: Include any industry-recognised certifications or relevant courses to strengthen your profile.
• Patents & intellectual property: If applicable, highlight innovations you’ve contributed to.
• Languages & right to work: Critical if you’re applying for roles abroad.

Keep these sections concise and relevant. The aim is to reinforce your professional strengths without overwhelming the reader with unnecessary detail.

AI product manager CV example: additional sections

6. Keep these formatting rules in mind for your AI product manager CV

A clear, scannable CV is essential for standing out in today’s competitive AI product management job market. Recruiters and hiring managers spend just a few seconds initially scanning each CV, so your AI product manager CV needs to be structured for readability and impact.

Writing a perfect CV means stripping away anything that doesn’t support your candidacy, highlighting measurable results, and presenting information in a format that works both for humans and Applicant Tracking Systems (ATS). With the right layout, you’ll ensure that your achievements – rather than clutter – take centre stage. 

Here’s how to format an AI PM CV:

• CV Length: 1 page for early-career, 1–2 pages for senior roles. Be ruthless: every line should support your candidacy.
• File format: send as PDF unless asked otherwise.
• Fonts & layout: use a clean, readable CV font (Calibri, Arial, or Helvetica) and clear subheadings.
• ATS: for an ATS-ready CV, mirror keywords from the job advert (e.g. “model deployment”, “A/B testing”, “MLOps”, “data pipelines”), but keep phrasing natural.
• Avoid fluff: skip vague claims like “passionate about AI” unless accompanied by demonstrable achievements.
• Contact details: put your name, role (e.g. AI Product Manager), email, phone, LinkedIn and a portfolio link at the top. No need for full address.
• Proofread: technical roles attract detail-oriented reviewers – eliminate typos and inconsistent formatting.

7. Support your AI product manager CV with a tailored cover letter

A strong AI product manager CV can get you noticed, but a tailored, short cover letter can set you apart. Think of it as the bridge between your CV and the company’s product challenges. Unless told otherwise, always include a cover letter, as 83% recruiters read them even if they’re not explicitly required. 

Here’s how to write a compelling AI product manager cover letter:

• Open your cover letter with impact: Reference the specific role and include a hook that shows why you’re a strong fit (e.g. a standout AI project or unique combination of skills).
• Highlight achievements: Select 2–3 relevant accomplishments from your CV, back them up with metrics, and show the value delivered (e.g. “launched NLP feature reducing triage time by 30%”).
• Show motivation: Explain why you want to join this company. Research their AI strategy, products, or industry context, and connect it to your background.
• Focus on outcomes: Emphasise how you’ll measure success in the role – whether that’s revenue impact, efficiency gains, or adoption rates.
• Close confidently: End your cover letter with a clear call to action, such as, “I would welcome the chance to discuss how I can help scale your AI products. I am available for an interview at your convenience.”

Keep the cover letter between 250 and 350 words, use proper cover letter formatting, and personalise the salutation if possible. Paired with an AI PM CV, it demonstrates not only what you’ve done but also why you’re the right person to drive the company’s AI product strategy forward.

You don’t have to be a CV writing expert. In the LiveCareer CV builder you’ll find ready-made content for every industry and position, which you can then add with a single click.

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Thank you for reading my article on how to write a CV for AI product manager jobs. If you’re interested in more expert tips on CV writing and career development, check out our blog for more articles!

How we review the content at LiveCareer

Our editorial team has reviewed this article for compliance with LiveCareer’s editorial guidelines. It’s to ensure that our expert advice and recommendations are consistent across all our career guides and align with current CV and cover letter writing standards and trends. We’re trusted by over 10 million job seekers, supporting them on their way to finding their dream job. Each article is preceded by research and scrutiny to ensure our content responds to current market trends and demand.

Sources

• The Ladders (2018), Eye-Tracking Study
• Harvard Business Review (2025), Cover Letters Still Matter—Even If They’re Not Required