Senior Data Engineer (with AI)

Provectus is a leading AI consultancy and AWS Premier Consulting Partner with 15+ years of R&D excellence. They deliver advanced solutions across AI, Data, ML, MLOps, and Cloud, recognized by Forrester and AWS (FinServ AI Competency). They partner with innovators like Anthropic and Cohere to build cutting-edge solutions from LLM-powered applications to next-gen data platforms across multiple industries. The company is expanding in Poland and seeks a Senior Data Engineer to join their EMEA team to drive high-impact AI and data projects alongside global experts.

Experience:

• 6+ years of hands-on engineering experience with production systems.
• Full-stack mindset across AI, Backend development, Data, and cloud infrastructure.
• Autonomous working style.
• Experience adopting AI tools in workflows (e.g., Claude Code, GitHub Copilot).
• Strong sense of ownership and proactivity.
• Openness to broadening skills into adjacent areas.
• B2+ English proficiency.

Data Engineering:

• Strong Python and SQL skills.
• Hands-on experience with Apache Spark.
• Proficiency with cloud data warehouses: Snowflake, Redshift, or ClickHouse.
• Experience building batch data workflows with Apache Airflow or similar.
• Experience with real-time data processing using Kafka and streaming frameworks.

LLMs & Generative AI / MLOps:

• Experience with LLM-based application patterns including RAG architectures, prompt design, and agentic workflows.
• Basic understanding of embedding models, vector databases, and semantic search.
• Awareness of LLM evaluation techniques and quality assurance.
• Experience deploying and maintaining ML models in production.
• Understanding of CI/CD practices applied to ML pipelines.

Cloud & Infrastructure:

• Hands-on experience with AWS services (SageMaker, Bedrock, Lambda, Glue, S3, ECR) or similar; GCP considered.
• Relevant cloud certifications are a plus.

• Design, build, and maintain robust data pipelines and ML systems for production environments.
• Develop and deploy ML and LLM-based solutions addressing real client business challenges.
• Build and maintain ETL/ELT workflows using modern orchestration and distributed computing tools.
• Implement MLOps practices: CI/CD, automated testing, model monitoring, and experiment tracking.
• Architect and implement cloud-native data and AI/ML solutions, primarily on AWS.
• Collaborate closely with Data Scientists, AI/ML Engineers, Backend Engineers, and client stakeholders.
• Participate in code reviews, contribute to technical documentation, and share knowledge within the team.
• Engage in client-facing discussions to understand requirements and propose technical solutions.