> DOU
senior
Codebridge Technology, Inc.Data Engineer
format:Remotecompany:Outsource
pythonsqlllmragprompt engineeringvector searchawsaws s3aws bedrockpostgresqlmachine learningeltetlany one ofeltdata lakedata modeling
databricksapache sparksnowflakemlops
> full description
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
- HR Interview
- Tech & Final Interviews
- Job Offer