Forward-Deployed AI Engineer: Build LLMs & Agents in Sports Tech

Sportradar; Województwo mazowieckie; On-site; PLN 180,000 - 280,000; Full time

Benefits offered by this job

Global team environment

Career development plan

Flexible working hours

Online training videos

Job summary

Sportradar is a world-leading sports technology company. We are seeking an Forward Deployed AI Engineer to work like an internal consultant, building and deploying LLM-powered solutions and agents.

You will collaborate with multiple teams, identify meaningful problems, and steer projects from prototype to production while handling data pipelines and retrieval systems. The role emphasizes independent work, strong Python fundamentals, and experience with LLM APIs and RAG.

Qualifications

• 2+ years of software engineering or applied ML experience
• Clear, non-technical communication with colleagues
• Self-motivated with ability to work independently
• Structured approach to finding problems and simplifying complexity
• Solid Python and software engineering fundamentals (testing, version control, APIs)
• Hands-on experience with LLM APIs and RAG/agents including evaluation
• Familiarity with SQL or data pipelines and a cloud platform (AWS, Azure or GCP)

Responsibilities

• Talk with colleagues to understand workflows and data
• Identify problems worth solving and break down complex situations
• Streamline processes and propose AI solutions where appropriate
• Work with stakeholders to keep work moving pragmatically
• Build, test, and deploy LLM-powered apps and agents from prototype to production
• Implement retrieval (RAG), tool integrations, prompts and context handling
• Build and maintain data pipelines feeding these systems
• Plan work and document solutions

Skills

Python

LLM APIs

SQL

Data Pipelines

Cloud Platforms

APIs

Testing

Version Control

Tools

Git

Docker

Job description

Sportradar is a world-leading sports technology company. We are seeking an Forward Deployed AI Engineer to work like an internal consultant, building and deploying LLM-powered solutions and agents.

You will collaborate with multiple teams, identify meaningful problems, and steer projects from prototype to production while handling data pipelines and retrieval systems. The role emphasizes independent work, strong Python fundamentals, and experience with LLM APIs and RAG.