Senior Data Engineer – AI Platform

Role Overview

• Integrate large language models into production AI agent workflows
• building structured-output pipelines with grounding, reference resolution, and evidence traceability.
• Design and evolve APIs that serve risk Intelligence data to customers and external integrations.
• Build and maintain data ingestion pipelines
• owning the full lifecycle from extraction through loading and error handling.
• Own reliability of async task processing systems — health monitoring, autoscaling, alerting, and incident response.
• Build and maintain shared libraries and internal developer tooling that accelerate the entire engineering team.
• Manage full service lifecycle — from standing up new services to decommissioning legacy ones.

Requirements

• 4+ years of experience in Data Engineering or Backend Engineering with a strong data focus.
• 4+ years of production Python experience
• you write clean, testable, well-structured code.
• Experience designing and building APIs (preferably GraphQL with Apollo Federation).
• Experience in developing, maintaining, and ensuring the reliability, scalability, fault tolerance, and observability of data services in a production environment.
• Have fundamental knowledge of data engineering techniques: ETL/ELT, batch and streaming, DWH, Data Lakes, distributed processing.
• Comfortable with async Python patterns (asyncio, Celery, task queues).
• Strong knowledge of SDLC and solid software engineering practices.
• Familiar with infrastructure-as-code approach.
• Demonstrated curiosity through asking questions, digging into new technologies, and always trying to grow.
• Strong problem solving and the ability to communicate ideas effectively.
• Self-starter, independent, likes to take initiative.
• Familiarity with at least some of the technologies in our current stack: Core: Python, Pandas, Polars, Celery, SQL (PostgreSQL), SQLAlchemy, Airflow, Docker, Kafka; AI/ML: OpenAI, Anthropic, Google Vertex AI, Pydantic (v2), Pydantic AI, MLflow; APIs: GraphQL (Strawberry); AWS: S3, Batch, RDS, DynamoDB, ECS, SQS, DMS, Lambda; Infra & Ops: Terraform, Datadog.
• Experience with or strong interest in AI-native development workflows (we use Claude Code as a core part of how we build software
• from building internal tooling skills to debugging production issues.

Tech Stack

• Airflow
• Apollo
• AWS
• Docker
• DynamoDB
• ETL
• GraphQL
• Kafka
• Pandas
• Postgres
• Python
• SDLC
• SQL
• Terraform

Benefits

• Option to work as a B2B contractor or full-time employee
• Competitive salary at a well-funded, fast-growing startup
• PTO days so you can take the time you need to refresh!
• Full-time employees: 28 PTO days allotted + paid public holidays
• B2B contractors: 15 PTO days allotted + paid public holidays
• 100% remote work (or hybrid if you prefer! We have coworking space in center of Warsaw.)