Back to SearchSenior AI Engineer with Spark, AWS Services
Remote in Türkiye
AI Solution Engineering
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We are seeking a Senior AI Engineer with Spark and AWS Services expertise to join the RBQM Production Pod within the program. You will build and maintain data pipelines that power AI/GenAI applications for Risk-Based Quality Management in clinical trials. This role focuses on RAG document ingestion, vector indexing, and building data APIs for AI applications.
Responsibilities
- Design and build RAG document ingestion pipelines (chunking, embedding, vector indexing) for clinical trial quality data
- Build and manage vector databases (AWS OpenSearch) for RAG-powered AI workflows
- Develop batch and streaming ETL/ELT pipelines from scratch for unstructured clinical data (PDF, DOCX, clinical reports)
- Build and expose data APIs for AI application consumption
- Optimize chunking strategies, embedding generation, and retrieval performance for RAG architectures
- Manage data quality, lineage, and governance for AI/ML data pipelines
- Deploy and maintain AWS data infrastructure (S3, Lambda, Glue, Athena, Step Functions, DynamoDB)
- Collaborate with Data Scientists and Backend Developers in an integrated pod team
Requirements
- 5+ years of hands-on data engineering experience at scale
- Expertise in RAG document ingestion pipelines (chunking, embedding, vector indexing)
- Proficiency in AWS OpenSearch as a vector database for RAG workflows
- Advanced proficiency in Python, including SQL and Spark SQL
- Skills in unstructured data transformation (PDF, DOCX) for RAG/LLM applications
- Familiarity with AWS Services: S3, Lambda, Glue, Athena, Bedrock, Step Functions, API Gateway, CloudWatch, DynamoDB
- Knowledge of containerization with Docker
- Capability to build custom pipelines from scratch, beyond configuring out-of-the-box services
- Proficiency in English at a B2+ level
Nice to have
- Background in pharmaceutical or life sciences domain
- Familiarity with Snowflake, Pinecone (vector DB alternative)
- Knowledge of SageMaker processing jobs
- Skills in CI/CD tools (Jenkins, Git/Bitbucket) and infrastructure tools (CDK or Terraform)
- Understanding of clinical data standards (CDISC, ADaM, SDTM)