Senior Data Engineer, AI

This is a fully remote position, open to applicants in Poland.

📋 Description

• Design, construct, and sustain resilient data pipelines and machine learning systems for production settings.

• Create and implement machine learning and LLM-based solutions that tackle genuine business challenges for clients.

• Develop and oversee ETL/ELT workflows utilizing contemporary orchestration and distributed computing tools.

• Apply MLOps methodologies: CI/CD, automated testing, model monitoring, and experiment tracking.

• Design and execute cloud-native data and AI/ML solutions, primarily utilizing AWS.

• Work closely with Data Scientists, AI/ML Engineers, Backend Engineers, and client stakeholders.

• Engage in code reviews, contribute to technical documentation, and disseminate knowledge within the team.

• Participate in client-facing discussions to grasp requirements and recommend technical solutions.

⛳️ Requirements

• Over 6 years of hands-on engineering experience with production systems, beyond just creating proofs of concept.

• Full-stack mindset, adept across AI, Backend development, Data, and cloud infrastructure.

• Independent working style — you advance projects without requiring extensive process oversight.

• Experience integrating AI tools into daily workflows (e.g., Claude Code, GitHub Copilot, or similar).

• Strong sense of ownership and initiative; you identify issues before they are brought to your attention.

• Willingness to expand skills into related areas.

• B2+ English proficiency, comfortable collaborating with distributed, multicultural teams.

• Proficient in Python and SQL, with solid software engineering fundamentals.

• Practical experience with Apache Spark for large-scale data processing.

• Familiarity with cloud data warehouse technologies: Snowflake, Redshift, or ClickHouse.

• Proven experience in building batch data workflows using Apache Airflow or similar orchestration tools.

• Experience in real-time data processing with Kafka and streaming frameworks.

• Familiarity with LLM-based application patterns, including RAG architectures, prompt design, and agentic workflows.

• Basic understanding of embedding models, vector databases, and semantic search.

• Knowledge of LLM evaluation techniques and quality assurance methods.

• Experience in deploying and maintaining machine learning models in production settings.

• Understanding of CI/CD practices as applied to ML pipelines.

• Practical experience with AWS (SageMaker, Bedrock, Lambda, Glue, S3, ECR, or similar); GCP experience is also considered. Relevant cloud certifications are advantageous.

🏝️ Benefits

• Meaningful work: projects encompass GenAI, MLOps, and NextGen data platforms for global enterprises in various industries.

• Senior-level colleagues: collaborate with leading ML and Data professionals across North America, LATAM, and EMEA.

• Career advancement: a clear path to Tech Lead for those with ambition — we actively foster our engineers' development.

• Recognized expertise: AWS Premier Consulting Partner featured in Forrester’s AI Technical Services Landscape.