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EVERSANA is a global commercialization services company serving the life sciences industry with 7,000+ employees across 650+ clients. This Senior Generative AI Engineer role is a hands-on technical position within the AI Hub Center of Excellence, focused on building production-grade AI agents and workflows for healthcare use cases.
You will design and build AI agents using Vertex AI Agent Builder, Claude API, and Gemini Enterprise, productionizing enterprise AI tooling for Patient Services workflows including intake automation, missing-information detection, adverse-event identification, workload queue intelligence, and claims chat integration. You'll develop and maintain RAG pipelines, vector stores, embeddings, and retrieval workflows against Patient Services data, implementing MCP server integrations and agent tool definitions that safely expose enterprise systems.
Integration is core to the role: you'll embed AI capabilities into Salesforce Health Cloud (Apex, LWC), MuleSoft (DataWeave), and Java SDLC touchpoints. You'll build reusable prompt templates and agent patterns for broader team adoption, contributing to a shared, version-controlled prompt/pattern library. You own the full agent lifecycle—build, deploy, monitor, evaluate, and retire—establishing evaluation harnesses to ensure quality gates before production. You'll monitor deployed agents for drift, cost, latency, and accuracy, and review AI-generated code from Salesforce, MuleSoft, and Java developers against ACTICS quality standards.
Required: 5+ years software engineering with production systems experience, advanced Python, JavaScript/TypeScript competence, hands-on cloud AI platform experience (Vertex AI preferred), demonstrated prompt engineering and LLM application development (Claude, Gemini, or equivalent), practical RAG and vector database experience, familiarity with agent orchestration frameworks (CrewAI, LangChain, LangGraph, Vertex Agent Builder), REST/GraphQL API integration experience. Salesforce and/or MuleSoft integration experience is a strong plus.
Preferred: MCP server and agent tooling standards experience, healthcare/life-sciences technology background with PHI/HIPAA awareness, Salesforce (Apex/LWC) or Java development, BigQuery or PostgreSQL experience. Stack includes Vertex AI, Claude, Gemini Enterprise, CrewAI, LangChain, LangGraph, GCP, BigQuery, PostgreSQL, and vector stores. First-year success includes shipping intake automation MVP and two additional AI workflow MVPs, establishing reusable agent patterns adopted by other engineers, and operationalizing agent evaluation and monitoring for all production agents.
