Senior Data Engineer / AI Specialist

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.

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

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

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

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

Recruitment Process

HR Interview

Tech & Final Interviews

Job Offer