Senior Data Engineer - AWS & RAG Pipelines

We're looking for a Senior Data Engineer to design and operate the cloud data infrastructure powering our AI initiatives. You'll architect production-scale data lakes on AWS, build real-time ingestion and observability pipelines, and own the vector search and embedding layers that feed our RAG systems and autonomous agents. Must-Have Overall Experience: 7+ years in Data Engineering, Distributed Systems, or Data Architecture AWS & Infrastructure: 4+ years architecting production-scale data lakes, storage tiers, and event streaming AI/LLM Pipelines: 2+ years building RAG systems, managing embeddings, and orchestrating foundational models Proficiency in AWS Data Lake Architecture & Storage Proficiency in Real-Time Observability & Log Analytics Proficiency in Elasticsearch & OpenSearch Optimization, Vectorization, Embeddings Proficiency in Amazon Bedrock & Generative AI Pipelines Proficiency in Software Engineering & API Ingestion Production-level proficiency in one or more of: C# (.NET Core), Java, Python, or Node.js Preferred Experience AWS S3 partitioning strategies, lifecycle policies, and columnar formats (Parquet, Iceberg) AWS Glue Data Catalog and Lake Formation for multi-tenant, fine-grained access control Query optimization over petabyte-scale datasets using Amazon Athena and Redshift Spectrum Distributed oTel collector configuration for log, trace, and metrics capture and routing into S3 High-volume streaming of system logs, Datadog captures, and raw server events into S3 Real-time CDC from PostgreSQL using Debezium or AWS DMS Amazon OpenSearch clusters with simultaneous lexical and high-dimensional vector search OpenSearch index lifecycle management, sharding strategies, and dynamic mappings at scale Amazon Bedrock foundational model APIs (Claude, Titan) for data enrichment, classification, and semantic parsing Knowledge Bases for Amazon Bedrock for automatic chunking, metadata extraction, and vector index syncs from S3 ETL/ELT pipelines ingesting unstructured event data from SaaS APIs (e.g., Pendo, Hotjar, Google Analytics) MCP server development to expose data lake context and utilities to AI agents Remote work. 13 floating holiday. 15 vacation days per year completed. Good working environment. Every qualified candidate who meets the requirements outlined in the job description will be considered in this hiring process without distinction. Furthermore, Jalasoft is an equal opportunity employer. We wholeheartedly embrace our responsibility to make employment decisions without regard to race, age, marital or social status, national origin, disability, sex, gender identity or expression, or any other characteristic or group of candidates or employees unrelated to their qualifications and suitability for the position. Our management is committed to upholding this policy with respect.