Senior Data Engineer / AI Specialist

Senior Data Engineer / AI Specialist

Сodebridge is 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

1. HR Interview

1. Tech & Final Interviews

1. Job Offer