We are looking for a Senior Data Engineer \/ AI Specialist (Agentic AI, AWS) to work on an enterprise AI platform MVP. You will build the data and AI layer: pipelines from multiple enterprise sources, a data lake, agentic AI use cases and predictive models.<\/p>\n
Responsibilities
Design and build ETL\/ELT pipelines from heterogeneous enterprise sources (ERP, planning, cost and schedule data, documents, external price indices)
Build and maintain the data lake \/ lakehouse; ensure data quality, modeling and governance
Develop agentic AI solutions: multi-agent orchestration, LLM integrations (AWS Bedrock), RAG over unstructured documents such as contracts
Build classical ML models, for example forecasting cost at completion from historical data
Evaluate AI output quality and reliability (evals, guardrails)
Ensure solutions comply with ISO 27001 \/ SOC 2 data security requirements
Work closely with the full-stack developer and the client's product and AI teams<\/p>\n
Requirements
5+ years in Data Engineering and\/or Applied AI
Strong Python and SQL
Practical experience with LLM applications: agents, RAG, prompt engineering, vector search, document processing
AWS: S3, Bedrock, data services; PostgreSQL
Experience with classical ML (regression, time-series forecasting)
Pipeline orchestration and data quality practices
Fluent English; availability for Central Europe \/ Middle East hours<\/p>\n
Nice to have
Databricks (likely platform for ETL and ML on this project), PySpark. Snowflake is also relevant
MLOps (model deployment, monitoring)
Experience with AI governance and data readiness
Domain knowledge of capital projects, cost management or contracts<\/p>\n
We Offer
Innovation Culture: Work in an AI-first team that actively experiments with agentic AI and modern development approaches
Meaningful Challenge: Build the data and AI foundation of an enterprise AI platform, from the data lake to production-ready AI agents and predictive models
Flexible Work: Remote work or a modern office in Kyiv
Generous Time Off: 20 paid vacation days + 15 sick leave days annually
Professional Growth: Compensation for courses, certifications (including AWS and Databricks), and learning resources
Cutting-Edge Tools: Access to premium AI tools (Cursor Pro, Claude Code, GitHub Copilot, etc.)
Supportive Environment: Collaboration, trust, and focus on outcomes rather than micromanagement<\/p>\n
Recruitment Process
HR Interview
Tech & Final Interviews
Job Offer<\/p>\n","protected":false},"excerpt":{"rendered":"
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