Senior AI Agent Engineer for Analytics Automation

Oracle; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Oracle Health is seeking a Senior AI Agent Engineer to build production AI agents and workflow automation capabilities that accelerate analytics delivery, improve insight generation, and reduce manual engineering work across our analytics and reporting ecosystem.

This engineer will design and implement AI-driven workflows that integrate with enterprise systems and support use cases such as SQL generation, pipeline scaffolding, data exploration, metric design support, insight discovery, executive

Qualifications

• 8+ years of software engineering experience with Python, APIs, and distributed systems.
• Expertise in AI agents and workflow automation, including tool calls and orchestration.
• Experience with GenAI, RAG, embeddings, and NL2SQL/conversational analytics.
• Proven production-ready AI systems with observability, validation, and security.
• Strong cross-functional collaboration across data, security, and infra teams.

Responsibilities

• Design, build, test, and deploy production AI agents and AI-assisted workflows.
• Implement agents that support SQL generation, pipeline creation, insight discovery, and dashboard scaffolding.
• Integrate AI capabilities with enterprise tools, data platforms, semantic services, and existing engineering workflows.
• Develop structured tool-calling patterns, validation logic, retry handling, and grounded output generation.
• Build evaluation and testing approaches for AI workflows, including regression testing.
• Partner with architects, semantic engineers, and domain teams to ensure AI outputs are useful, accurate, and operationally practical.
• Optimize workflows for quality, speed, cost, and maintainability.
• Contribute to AI engineering standards, reusable components, and continuous improvement across the team.
• Foundation-model access, model routing, inference, embeddings, reranking, fine-tuning, prompt/context management, and model lifecycle.
• Agent runtimes, multi-agent orchestration, planning, memory, tool execution, workflow integration, human approvals, and secure delegation.
• Retrieval-augmented generation (RAG), knowledge bases, semantic and hybrid search, query rewriting, reranking, grounding, provenance, and citations.
• Enterprise knowledge management including ingestion, parsing, chunking, metadata, taxonomy, ontology, business glossary, lifecycle, and entitlement-aware retrieval.
• NL2SQL and conversational analytics, including schema/semantic grounding, metadata enrichment, SQL generation and validation, permission-aware execution, and natural-language narration of results.
• AI-ready data platforms supporting batch, streaming, change data capture, lakehouse patterns, data products, feature/embedding generation, and low-latency serving.
• AI evaluation and observability covering quality, hallucination/grounding, retrieval relevance, tool-call success, agent completion, latency, reliability, safety, and cost.
• AI security and governance including identity, authorization, tenant isolation, private networking, secrets, auditability, data residenc

Skills

Python

APIs

Distributed systems

Production-grade

AI agents

Tool orchestration

LLM integration

Cross-functional collaboration

Tools

OCI Generative AI

Oracle AI Database/Vector Search

OpenSearch

RAG

Embeddings

Job description

Oracle Health is seeking a Senior AI Agent Engineer to build production AI agents and workflow automation capabilities that accelerate analytics delivery, improve insight generation, and reduce manual engineering work across our analytics and reporting ecosystem.

This engineer will design and implement AI-driven workflows that integrate with enterprise systems and support use cases such as SQL generation, pipeline scaffolding, data exploration, metric design support, insight discovery, executive