Jobs via Dice ยท 10 hours ago
Agentic AI Developer@Berkeley Heights, NJ (5 days onsite)
Berkeley Heights, NJ
Full-time
Onsite
Mid, Senior LevelDice is the leading career destination for tech experts at every stage of their careers, and they are seeking an Agentic AI Developer to join Enexus Global. The role involves building and productionizing Vertex AI based RAG systems, designing reliable tool-using agents, and managing end-to-end delivery of various AI projects.
Computer Software
Responsibilities
Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking, embeddings, indexing, retrieval, reranking, grounding)
Build agentic workflows (tool use, planning, reflection/guardrails, structured outputs) using Python-first frameworks
Integrate agents with Graph DBs (e.g., Neo4j, JanusGraph, Neptune) and Vector DBs (e.g., Vertex Vector Search, Pinecone, Weaviate, Milvus, pgvector)
Create robust data ingestion/ETL from PDFs, docs, webpages, and internal sources; implement metadata strategy and access control
Define and run evaluation (retrieval metrics, answer quality, hallucination/grounding checks), and improve system quality iteratively
Ship to production: APIs, monitoring/observability, cost/performance optimization, CI/CD, and security best practices
Qualification
Required
Strong Python (clean architecture, async, testing, typing, packaging)
Proven experience building RAG solutions (hybrid search, reranking, chunking strategies, embeddings, prompt + schema design)
Hands-on with Vertex AI and Google Cloud Platform fundamentals (IAM, logging/monitoring, Cloud Run/GKE, storage)
Experience with at least one agentic framework (e.g., LangGraph/LangChain, LlamaIndex, Semantic Kernel, AutoGen) and tool/function calling patterns
Solid knowledge of vector search concepts and at least one vector DB in production
Comfortable with graph data modeling and graph querying (Cypher/Gremlin/SPARQL basics)
Strong engineering practices: code reviews, testing, telemetry, secure-by-design, reliability mindset
Preferred
Knowledge graphs for RAG (entity linking, graph traversal + retrieval fusion)
Streaming/messaging (Pub/Sub, Kafka), document pipelines (Document AI), and multilingual retrieval
Experience with evaluation tooling (RAGAS, TruLens, custom eval harnesses), prompt/version management
Frontend integration (basic React/Next.js) or platform enablement (internal developer tooling)
Company
Jobs via Dice
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Funding
Current Stage
Early StageCompany data provided by crunchbase