Time since we first saw it
Day 52
Similar jobs usually come down between day 4 and day 77.
From 51 similar postings that came down. Coming down is not always a hire.
AI Data Engineer
Reads like an AI Engineer role: building products on existing AI models.
Prague (Hybrid)
Live, first seen by us 52 days ago- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Listed location: Prague (Hybrid)
Work setup in the employer’s posting: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
Before you apply
- Work authorization
- Must already have the right to work in the EU
Candidates must have the legal right to work in the EU
What you’ll work on
Full postingDesign and deploy multi-agent workflows that reason, use tools and surface insights
Build the data model and semantic layer that AI agents rely on for context
Build evaluation frameworks and monitoring so agent outputs stay accurate and safe
Develop dbt models and Snowflake pipelines for revenue, marketing and product reporting
Investigate and resolve data quality issues and handle stakeholder ad-hoc requests
From the employer’s posting
Design and deploy multi-agent workflows that can reason, use tools, and provide proactive insights across internal domains.
Shape the data model and build a semantic layer that serves as the clean context our AI agents depend on.
Build evaluation frameworks and monitoring suites so agent outputs stay accurate, governed, and safe
Develop the dbt models and Snowflake pipelines that power reporting across revenue, marketing, and product events.
Investigate and resolve data quality issues, support stakeholders with ad-hoc requests
What you’ll bring
All qualificationsCore experience
- Experience: 18+ months in data engineering, analytics engineering, or a similar role.
- Experience building AI agents or LLM-powered workflows with frameworks such as the Claude Agent SDK, LangGraph, or PydanticAI.
- SQL and Python: Strong hands-on experience building and maintaining Python and SQL pipelines.
- Experience building an AI agent-native semantic layer.
- Experience running large data warehouses, data lakes, or lakehouses in production.
- Familiarity with orchestration or ETL platforms such as Keboola, Airflow, or similar.
Qualification wording
Experience: 18+ months in data engineering, analytics engineering, or a similar role.
Experience building AI agents or LLM-powered workflows with frameworks such as the Claude Agent SDK, LangGraph, or PydanticAI.
SQL and Python: Strong hands-on experience building and maintaining Python and SQL pipelines.
Experience building an AI agent-native semantic layer.
Experience running large data warehouses, data lakes, or lakehouses in production.
Familiarity with orchestration or ETL platforms such as Keboola, Airflow, or similar.
Education & alternatives
- Quality-minded: You care about testing, maintainability, and reliability, and you're comfortable with Git, code review, and CI/CD fundamentals. - Education: Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related quantitative discipline. - Collaborative: You work well in a fast-moving, cross-functional, multinational environment, and communicate clearly in English.
About Productboard
Productboard is the leading intelligent product management platform, used by 6,000+ companies including Salesforce, SAP, Autodesk, and Kroger.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 22, 202652 days ago
- Recorded sightings
- 22
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Productboard is hiring
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- dbt
- Docker
- Looker
- Power BI
- Snowflake
- Tableau
- Terraform
- Airflow
Where the posting names them
- Fluent with AI coding tools: You use tools like Claude Code, Cursor, or GitHub Copilot in your daily workflow, and know where they speed you up without lowering your standards. - SQL and Python: Strong hands-on experience building and maintaining Python and SQL pipelines. - dbt and cloud warehousing: Hands-on experience with dbt and production ETL pipelines, and familiarity with a modern cloud data platform such as Snowflake.
- Engineering practices: GitHub for version control, code review, and CI/CD via GitHub Actions. - Languages: SQL for dbt-powered transformation, Python for pipeline logic and tooling. You'll deepen both here. - Analytics and event tracking: Looker, Amplitude, and Segment.
- Exposure to analytics platforms such as Looker, Power BI, or Tableau. - Experience with AWS. - Familiarity with Docker, Terraform IaaC, or other DevOps tooling.
- AI ecosystem: an internal agentic platform built on frontier models, the Claude Agent SDK, and custom MCP servers. - Data foundation: Snowflake, dbt, Keboola, and AWS. - Engineering practices: GitHub for version control, code review, and CI/CD via GitHub Actions.
- Make agents reliable and fast to ship. Build evaluation frameworks and monitoring suites so agent outputs stay accurate, governed, and safe, and create reusable patterns that move prototypes to production quickly. - Build and maintain pipelines. Develop the dbt models and Snowflake pipelines that power reporting across revenue, marketing, and product events. - Keep data trustworthy. Investigate and resolve data quality issues, support stakeholders with ad-hoc requests, and adopt (then help evolve) the team's practices around testing, documentation, and monitoring.
- SQL and Python: Strong hands-on experience building and maintaining Python and SQL pipelines. - dbt and cloud warehousing: Hands-on experience with dbt and production ETL pipelines, and familiarity with a modern cloud data platform such as Snowflake. - Quality-minded: You care about testing, maintainability, and reliability, and you're comfortable with Git, code review, and CI/CD fundamentals.
- Experience with AWS. - Familiarity with Docker, Terraform IaaC, or other DevOps tooling. - Experience in a fast-moving AI-native SaaS company.
- Familiarity with orchestration or ETL platforms such as Keboola, Airflow, or similar. - Exposure to analytics platforms such as Looker, Power BI, or Tableau. - Experience with AWS.
- Experience running large data warehouses, data lakes, or lakehouses in production. - Familiarity with orchestration or ETL platforms such as Keboola, Airflow, or similar. - Exposure to analytics platforms such as Looker, Power BI, or Tableau.
Your next step
Complete your application on jobs.gem.com. The employer’s form will show what is required.
Already applied? Track this application
Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
Productboard is looking for an AI Data Engineer to join our Data Engineering team. You'll help build AI-native data engineering agents and a platform behind Productboard's analytics and business operations. You’ll help unlock AI-enabled analytics for fast and precise self-service data analytics.
You are already an AI-native builder, experienced in modern data engineering, and you want to blend those fields together. You'll start by working alongside experienced engineers to implement AI-first analytics, streamline and optimize data pipelines, and progressively take ownership of your own area, including our internal AI platform.
What you will do
- Build Agentic Systems: Design and deploy multi-agent workflows that can reason, use tools, and provide proactive insights across internal domains.
- Engineer LLM-ready data. Shape the data model and build a semantic layer that serves as the clean context our AI agents depend on.
- Make agents reliable and fast to ship. Build evaluation frameworks and monitoring suites so agent outputs stay accurate, governed, and safe, and create reusable patterns that move prototypes to production quickly.
- Build and maintain pipelines. Develop the dbt models and Snowflake pipelines that power reporting across revenue, marketing, and product events.
- Keep data trustworthy. Investigate and resolve data quality issues, support stakeholders with ad-hoc requests, and adopt (then help evolve) the team's practices around testing, documentation, and monitoring.
- Contribute to how we work. Take part in code review, testing, deployment, and monitoring, and take ownership of part of it over time. Work directly with Analytics, BizOps, Product, and Engineering on what they need from the data.
About You
- Experience: 18+ months in data engineering, analytics engineering, or a similar role.
- Fluent with AI coding tools: You use tools like Claude Code, Cursor, or GitHub Copilot in your daily workflow, and know where they speed you up without lowering your standards.
- SQL and Python: Strong hands-on experience building and maintaining Python and SQL pipelines.
- dbt and cloud warehousing: Hands-on experience with dbt and production ETL pipelines, and familiarity with a modern cloud data platform such as Snowflake.
- Quality-minded: You care about testing, maintainability, and reliability, and you're comfortable with Git, code review, and CI/CD fundamentals.
- Education: Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related quantitative discipline.
- Collaborative: You work well in a fast-moving, cross-functional, multinational environment, and communicate clearly in English.
Nice to Have
- Experience building AI agents or LLM-powered workflows with frameworks such as the Claude Agent SDK, LangGraph, or PydanticAI.
- Experience building an AI agent-native semantic layer.
- Experience running large data warehouses, data lakes, or lakehouses in production.
- Familiarity with orchestration or ETL platforms such as Keboola, Airflow, or similar.
- Exposure to analytics platforms such as Looker, Power BI, or Tableau.
- Experience with AWS.
- Familiarity with Docker, Terraform IaaC, or other DevOps tooling.
- Experience in a fast-moving AI-native SaaS company.
Our Tech Stack
- AI ecosystem: an internal agentic platform built on frontier models, the Claude Agent SDK, and custom MCP servers.
- Data foundation: Snowflake, dbt, Keboola, and AWS.
- Engineering practices: GitHub for version control, code review, and CI/CD via GitHub Actions.
- Languages: SQL for dbt-powered transformation, Python for pipeline logic and tooling. You'll deepen both here.
- Analytics and event tracking: Looker, Amplitude, and Segment.
Our Compensation
Salary range: 1,000,000–1,680,000 CZK annually
Our benefits include
- Stock options
- MacBook + 34″ monitor
- Work from home stipend to support your home office setup
- 5 weeks of vacation + 9 sick days
- Flexible working hours and home office
- Budget for online courses, books, and conferences
- 2 weeks of fully paid parental leave
- Fertility & Family-Building Support with Carrot
- Mental Wellness Program with Soulmio to support your well-being and self-care
- 1 Volunteer Day per year to support causes close to your heart, plus donation matching from Productboard
- Free snacks, drinks, and yummy catered lunches from White Circus at the office every day
- Free MultiSport card
- On-site bouldering wall, boxing bag, and workout mats
- Team events, such as happy hours, off-sites, and retreats
- Free year-round access to Prague Zoo
Relocation Opportunities
If joining us means making a move, we're here to help make that transition easier.
Candidates must have the legal right to work in the EU. While we are unable to provide visa sponsorship for this role, we're happy to support relocation to Prague for candidates already authorized to work in the EU.
Relocation Support
We offer a one-time relocation bonus ranging from $6,000 to $13,000 USD, depending on your personal situation, whether you're moving on your own or with a partner or family.
This bonus is intended to help offset moving expenses and support your transition into your new city. While it may not cover every cost, it provides meaningful financial support as you get settled.
If you're thinking about relocating and want to explore what this could look like for you, we'd be happy to have that conversation.
About Productboard
Productboard is the leading intelligent product management platform, used by 6,000+ companies including Salesforce, SAP, Autodesk, and Kroger. Headquartered in San Francisco, with engineering hubs in Prague and Brno. Backed by Index Ventures, Kleiner Perkins, Sequoia Capital, Bessemer, Tiger Global, and Dragoneer.
We've spent the last decade building the foundation for how product teams work. We're now in our 0-to-1 moment again, building Productboard Spark — the AI-first, agentic experience that turns raw feedback and signals into clear problems, strong specs, and faster execution. Spark is what powers everything you'd be working on.
Are you building with us?
If the work above is what you want to spend the next chapter of your career on, apply below!
Equal Opportunity
Productboard is an equal opportunity employer. We are committed to an inclusive hiring process and consider all qualified applicants without discrimination based on characteristics protected by applicable law. If you require an accommodation during the hiring process, please contact peopleops@productboard.com.
By applying you agree to Productboard's Global Candidate Privacy Policy
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Prague (Hybrid)
- Free MultiSport card - On-site bouldering wall, boxing bag, and workout mats - Team events, such as happy hours, off-sites, and retreats
- Work authorization
If joining us means making a move, we're here to help make that transition easier. Candidates must have the legal right to work in the EU. While we are unable to provide visa sponsorship for this role, we're happy to support relocation to Prague for candidates already authorized to work in the EU. Relocation Support