Senior AI Data Engineer

Apexon is looking for a Senior Data Analytics & Knowledge Engineer to join our growing AI and Data Engineering team. This is a hands‑on engineering role focused on building AI‑ready data foundations for next‑generation AWS Agentic AI applications in the Life Sciences and Healthcare domain.

You'll work at the intersection of Data Engineering, Knowledge Graphs, Semantic AI, and Generative AI, enabling intelligent agents to retrieve, reason over, and generate accurate responses from enterprise knowledge.

What You'll Do

• Design and build scalable data ingestion and transformation pipelines using Python and AWS services.
• Create AI‑ready datasets from structured and unstructured enterprise data.
• Build and manage knowledge graphs, ontologies, taxonomies, and semantic models to represent business entities and relationships.
• Develop graph‑based retrieval solutions using Amazon Neptune (or Neo4j experience).
• Build Retrieval‑Augmented Generation (RAG) pipelines using vector search technologies such as Amazon Open Search Service.
• Implement semantic chunking, embeddings, metadata enrichment, and grounding strategies for LLM applications.
• Develop LLM‑powered applications using Amazon Bedrock, prompt engineering, and RAG frameworks.
• Build Text-to-SQL capabilities for natural language querying over governed datasets.
• Work with AWS Glue Data Catalog, Amazon S3/S3 Tables, and Apache Iceberg to create discoverable and governed data assets.
• Collaborate with AI Engineers, Solution Architects, and Data/ML teams to improve retrieval quality, lineage, and production readiness.

Required Skills

• 8 years of experience in Data Engineering, Knowledge Engineering, or AI Engineering.
• Strong programming experience in Python and SQL.
• Hands‑on experience with Amazon Neptune or Neo4j.
• Experience designing Knowledge Graphs, ontologies, and semantic data models.
• Good understanding of RDF, OWL, SKOS, and Turtle (.ttl) files.
• Experience building RAG applications using vector search and embeddings.
• Hands‑on experience with Amazon Bedrock and AWS AI services.
• Experience with AWS Glue, Amazon S3, Apache Iceberg, and cloud data architectures.
• Experience using Lang Chain, Llama Index, or similar GenAI orchestration frameworks.
• Understanding of Text-to-SQL implementation and LLM integration patterns.

Nice to Have

• Experience with Databricks or lakehouse architectures.
• Exposure to Life Sciences, Healthcare, or Pharmaceutical data.
• Experience with metadata management, data lineage, governance, and AI‑ready data preparation.
• Familiarity with Strands Agents or agentic AI frameworks.