# AI Product Manager Resume Template (English)

> This is a blank template, not a case study or hiring standard for any company. Use only truthful, disclosable experience and results that you can explain. Do not invent internships, users, launch states, metrics, or ownership. Delete irrelevant sections instead of manufacturing content to fill a page.

How to use it: choose one current target job description, map its tasks, objects, constraints, and expected outcomes to your evidence, and then fill the template. Export a PDF and test text, contact details, and portfolio links while signed out.

---

# {{Name}}

**Target direction:** {{for example: AI Product Manager | Knowledge assistant / Agent workflow / AI application}}

**Contact:** {{email}} | {{phone, optional}} | {{location, optional}}

**Portfolio:** {{publicly accessible URL}} | **Other:** {{LinkedIn / GitHub / personal site, optional}}

## Summary (optional)

Use three to five lines to state the target context, inspectable capability, strongest evidence, and current experience boundary. Avoid unsupported words such as “expert,” “industry-leading,” or “significantly improved.”

> {{I have completed … tasks in … contexts, personally owning …; the evidence for … includes …; my work on … remains at the practice / prototype / pilot stage.}}

## Education

### {{Institution}} | {{Degree and field}}

{{Start month/year}} – {{End or expected graduation}} | {{Location, optional}}

- {{Relevant course, research, or project; remove if it adds no evidence}}
- {{Award or ranking only when accurate, verifiable, and relevant}}

## Relevant experience

### {{Organization or project}} | {{Accurate title / role}}

{{Start month/year}} – {{End month/year}} | {{Full-time / internship / campus / volunteer, optional}}

- **Task:** {{Who needed to complete what, and in which context}}
- **Evidence:** {{Research, data, workflow observation, baseline, or constraint; include source and scope}}
- **Personal scope:** {{Decisions, collaboration, and artifacts you owned; distinguish others' work}}
- **Action and trade-off:** {{Options compared and why one was selected or rejected}}
- **Outcome and limit:** {{Truthful result, validation conclusion, or delivery state; define metric and window; label anything not launched}}

### {{Second organization or project}} | {{Accurate title / role}}

{{Start month/year}} – {{End month/year}}

- {{Use the task–evidence–scope–action–outcome structure for relevant facts}}
- {{Keep only facts that can survive follow-up and match the target role}}

## AI product project

### {{Project name}} | {{State: personal practice / course / internship / prototype / pilot / live}}

{{Start month/year}} – {{End or present}} | [{{Portfolio or demo, optional}}]({{URL}})

**One-sentence task**

{{Who transforms which input into what output, in which context; which decisions remain outside AI.}}

**Problem evidence and baseline**

- Current workflow: {{How a person, rule, search, template, or existing product completes it}}
- Problem evidence: {{Authorized research, public material, workflow observation, or synthetic exercise source and limits}}
- Non-AI baseline: {{Quality, time, steps, or risk without the model}}

**Individual contribution**

- I owned: {{Truthful task definition, research, evaluation, prototype, metric, alignment, or retrospective work}}
- Others owned: {{Design, engineering, analytics, business, or mentor contribution; remove when irrelevant}}
- Tool assistance: {{What a model or automation generated and how you checked it}}

**Product design and boundaries**

- AI role: {{Generate / extract / classify / rank / recommend / call tools}}
- Exclusions: {{Unsupported input, user, data, or high-impact decision}}
- Control and recovery: {{Sources, edit, reject, confirm, human escalation, fallback, or rollback}}

**Evaluation and failure**

- Evaluation set: {{Case provenance, version, and slices; label synthetic data}}
- Rubric: {{Observable task completion, faithfulness, boundary handling, or other criteria}}
- Critical failure: {{For example unsupported output or unauthorized action; tailor to the task}}
- Finding: {{Only truthful, disclosable observations; use an evaluation plan when results do not exist}}
- Failure taxonomy: {{Observed error types and how they changed the next version}}

**Cost, latency, and release decision**

- Cost: {{Model, retrieval, tools, retry, and human effort per successful task}}
- Latency: {{End-to-end definition, P50/P95, or an explicitly unvalidated target}}
- Decision: {{Continue, narrow, fall back, or stop, and the evidence}}

**One resume bullet**

> {{For “user and task,” used “problem evidence / baseline” to identify “specific issue.” I owned “scope,” compared “options and trade-off,” and delivered “artifact.” Through “evaluation / validation,” found “truthful conclusion” while retaining “limit and next step.”}}

### {{Second project, optional}} | {{Accurate project state}}

Repeat the project structure only when a second project supplies different capability evidence. Do not occupy space with two nearly identical demos.

## Skills

- **Product:** {{Task framing, research, requirements, prototype; prepare an artifact for each}}
- **Data and evaluation:** {{SQL, metrics, evaluation set, rubric; list only explainable capability}}
- **AI systems:** {{RAG diagnosis, agent tool boundaries, model API; avoid a model-name inventory}}
- **Tools:** {{Tool + real use, not a self-rating}}
- **Languages:** {{Language and verifiable level, optional}}

## Truthfulness and readability check

- [ ] Every organization, title, and date is accurate and consistent
- [ ] Practice, prototype, pilot, and live states are clearly distinguished
- [ ] Every number has a definition, scope, version, time window, and permission to disclose
- [ ] Team outcomes are not presented as individual outcomes
- [ ] Automated model grades are not presented as human review or user outcomes
- [ ] No users, interviews, customers, revenue, conversion, or success rate is invented
- [ ] Unauthorized internal files, raw customer text, secrets, and screenshots are removed
- [ ] Skills match the target role and have supporting artifacts or explanations
- [ ] PDF text is selectable, reading order works, and links open while signed out
- [ ] Filename, contact details, dates, and language have been checked

## Project deep-dive notes (do not place on the resume)

For every retained project, write:

1. {{Most important product judgment and its evidence}}
2. {{One rejected option and why}}
3. {{Most critical failure and recovery}}
4. {{One artifact you personally completed}}
5. {{A conclusion the project cannot currently support}}
6. {{The first assumption you would test if restarting}}

Template updated: 2026-08-20