Data Engineer - Senior Consultant level
$152,200–$243,700 year
Hybrid · Bellevue, Washington, United States
Job Summary
Design and build scalable data platforms powering GenAI applications, AI agents, semantic search, and retrieval-augmented generation (RAG); develop high-throughput real-time and batch data pipelines; build vector indexing, embedding pipelines, semantic retrieval, and intelligent context management; engineer backend services and APIs for orchestration workflows and enterprise automation; collaborate with product teams to deliver secure, production-grade AI data capabilities; explore emerging GenAI infrastructure and cloud-native architectures. This is a hybrid role with in-office days to be confirmed by the Hiring Manager.
Required Qualifications
- 5+ years of relevant work experience with a bachelor’s degree -or- At least 2 years of work experience with an Advanced degree (e.g., Masters, MBA, JD, MD) -or- 0 years of work experience with a PhD.
- Preferred Qualifications: Four (4) years of experience solving data problems using data technologies (e.g., Hadoop, Hive, Kafka, Redis, NoSQL, RDBMS).
- Experience building enterprise GenAI platforms, semantic search systems, or AI data infrastructure.
- Experience with vector databases, embedding pipelines, retrieval optimization, or knowledge graph systems.
- Experience implementing observability, lineage, evaluation, and governance frameworks for AI-enabled data systems.
- Familiarity with cloud-native AI infrastructure and scalable ML/data platform architectures.
- Exposure to payments, fintech, or highly regulated enterprise environments with stringent security and reliability requirements.
- AI-Native Data Engineering; Distributed Data Systems; Retrieval & Knowledge Infrastructure; Real-Time Data Engineering; Production Platform Engineering; Backend & API Engineering; Cloud-Native Infrastructure; Data + AI Systems Thinking.
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