Pay: Salary not listed in the saved posting
Work setup: Hybrid stated — work setup source
Listed location: Prague (Hybrid)
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Employment: Unconfirmed

Before you apply

Sponsorship: Visa sponsorship not confirmed — sponsorship source
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.
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Apply at Productboard, Inc

What you’ll work on

Full posting

Build Agentic Systems: Design and deploy multi-agent workflows that can reason, use tools, and provide proactive insights across internal domains.
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.

From the employer’s posting

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.

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.

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.

What you’ll bring

All qualifications

Core 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.

Tools in this posting

Python
SQL
dbt
Docker
Looker
Snowflake
Terraform
Airflow
AWS
Power BI
Tableau

Source

- 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.

- 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.

- 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.

- 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.

- Exposure to analytics platforms such as Looker, Power BI, or Tableau. - Experience with AWS. - Familiarity with Docker, Terraform IaaC, or other DevOps tooling.

About Productboard, Inc

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

Job description

View original posting ↗

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

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Source & posting history

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Source excerpts

Selected 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

Open source at jobs.gem.com ↗Read the full description ↓

Status in our records: Active
First seen by us: Sep 22, 2026
Recorded sightings: 4
Last seen by us: Oct 2, 2026

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