Sr AI Solutions Engineer (Generative AI & Agentic AI)

EVERSANA

21h

About The Position

The AI Solutions Engineer is a hands-on builder within the AI Hub Center of Excellence. This role translates architectural direction and governance into working, production-grade agents and AI workflows utilizing EVERSANA's enterprise AI stack, including GCP, Vertex AI, Claude, and Gemini Enterprise. The engineer will productionize enterprise AI tooling for Patient Services use cases, develop reusable patterns for other teams, and integrate AI into Salesforce, MuleSoft, and Java touchpoints within the Software Development Life Cycle (SDLC). This is a deeply technical role focused on building real AI systems in a regulated healthcare environment, rather than just experimentation.

Requirements

• 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.
• Comfortable working on a follow-the-sun model with an onshore lead.

Nice To Haves

• Salesforce and/or MuleSoft integration experience.
• 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.

Responsibilities

• 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, including 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 to safely expose enterprise systems to agents.
• Integrate AI capabilities into Salesforce Health Cloud (Apex, LWC), MuleSoft (DataWeave), and Java SDLC touchpoints.
• Build reusable prompt templates and agent patterns for adoption by the broader engineering team.
• Contribute to the shared prompt/pattern library with quality-reviewed, version-controlled components.
• Own the agent lifecycle end to end: build, deploy, monitor, evaluate, and retire.
• Establish evaluation harnesses to test agents against defined quality bars before production.
• Review AI-generated code produced by Salesforce, MuleSoft, and Java developers to ensure it meets ACTICS quality standards.
• Monitor deployed agents for drift, cost, latency, and accuracy, and remediate as needed.

Benefits

• Certified as a Great Place to Work across the globe

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed