01Overview
Company DescriptionAt EVERSANA, we are proud to be certified as a Great Place to Work across the globe. Were fueled by our vision to create a healthier world. How Our global team of more than 7,000 employees is committed to creating and delivering next-generation commercialization services to the life sciences industry. We are grounded in our cultural beliefs and serve more than 650 clients ranging from innovative biotech start-ups to established pharmaceutical companies. Our products, services and solutions help bring innovative therapies to market and support the patients who depend on them. Our jobs, skills and talents are unique, but together we make an impact every day. Join us!
Across our growing organization, we embrace diversity in backgrounds and experiences. Improving patient lives around the world is a priority, and we need people from all backgrounds and swaths of life to help build the future of the healthcare and the life sciences industry. We believe our people make all the difference in cultivating an inclusive culture that embraces our cultural beliefs. We are deliberate and self-reflective about the kind of team and culture we are building. We look for team members that are not only strong in their own aptitudes but also who care deeply about EVERSANA, our people, clients and most importantly, the patients we serve. We are EVERSANA.
Job DescriptionThe AI Solutions Engineer is the hands-on builder of the AI Hub Center of Excellence. Where the AI Engineering & Enablement Lead sets architecture and governance, this role turns that direction into working, production-grade agents and AI workflows that ride on EVERSANA's enterprise AI stack (GCP, Vertex AI, Claude, Gemini Enterprise).
This engineer productionizes enterprise AI tooling for Patient Services use cases, builds the reusable patterns other teams depend on, and integrates AI into the Salesforce, MuleSoft, and Java touchpoints of our SDLC. It is a deep technical role for someone who wants to build real AI systems in a regulated healthcare environment, not just experiment.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
Agent & Workflow Development
Design and build AI agents on Vertex AI Agent Builder, the Claude API, and Gemini Enterprise.Productionize enterprise AI tooling for priority Patient Services use cases: intake automation, missing-information workflow, adverse-event detection, workload queue intelligence, QNCR automation, and chat-with-claims.Build and maintain RAG pipelines, vector stores, embeddings, and retrieval workflows against Patient Services data.Implement MCP server integrations and agent tool/function definitions that expose enterprise systems to agents safely.
Integration & SDLC
Integrate AI capabilities into Salesforce Health Cloud (Apex, LWC), MuleSoft (DataWeave), and Java SDLC touchpoints.Build reusable prompt templates and agent patterns that the broader engineering team can adopt.Contribute to the shared prompt/pattern library with quality-reviewed, version-controlled components.
Lifecycle & Quality
Own the agent lifecycle end to end: build, deploy, monitor, evaluate, and retire.Establish evaluation harnesses so agents are tested against defined quality bars before production.Review AI-generated code produced by Salesforce, MuleSoft, and Java developers, ensuring it meets ACTICS quality standards.Monitor deployed agents for drift, cost, latency, and accuracy; remediate as needed.
QualificationsMINIMUM KNOWLEDGE, SKILLS AND ABILITIES:
5+ years in software engineering, with hands-on experience building production systems.Advanced Python; competence in JavaScript/TypeScript.Direct experience with a cloud AI platform (Vertex AI strongly preferred) and its SDK.Demonstrated prompt engineering and LLM application development with Claude, Gemini, or equivalent models.Practical experience with RAG, vector databases, embeddings, and retrieval design.Familiarity with agent orchestration frameworks (CrewAI, LangChain, LangGraph, or Vertex Agent Builder).Experience integrating with REST/GraphQL APIs; Salesforce and/or MuleSoft integration experience a strong plus.Comfortable working on a follow-the-sun model with an onshore lead.
Preferred Qualifications
Experience with MCP (Model Context Protocol) servers and agent tooling standards.Background in healthcare or life-sciences technology; awareness of PHI/HIPAA constraints.Salesforce (Apex/LWC) or Java development experience.Experience with BigQuery, PostgreSQL, or comparable data platforms.
Tools & Stack
AI: Vertex AI Agent Builder, Claude API, Gemini Enterprise API.Orchestration: CrewAI, LangChain, LangGraph.Dev productivity: Claude Code, Cursor, GitHub Copilot.Data & cloud: GCP, BigQuery, PostgreSQL, vector stores.
First-Year Success Measures
Intake Automation MVP and at least two additional AI workflow MVPs built and shipped to one or more programs.Reusable agent patterns and prompt library established and adopted by other engineers.Agent .
