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EVERSANA is establishing an AI Hub Center of Excellence within Patient Services Technology to transform software development practices. The AI Engineering & Enablement Lead will own this strategic mission: ingesting enterprise AI tooling into the Patient Services SDLC, building a governed framework for deploying and maintaining AI agents, establishing engineering best practices, and re-architecting the organization into an AI-augmented software development operation.
This is a player-coach role requiring both hands-on technical leadership and team management. The Lead serves as the onshore anchor of a hybrid team, running stakeholder alignment, architecture decisions, and governance during US business hours while an offshore team executes build and test activities. You will be accountable for converting the AI Hub roadmap from a backlog of capabilities into shipped, governed, production-grade software delivered by an AI-accelerated team.
Key responsibilities include:
Enablement & SDLC Transformation: Own the AI Hub COE charter and bridge EVERSANA's Enterprise AI team with Patient Services engineering. Operationalize enterprise AI tooling (GCP Vertex AI, Claude, Gemini Enterprise) into daily SDLC workflows for ACTICS (Salesforce Health Cloud), MuleSoft, and Java/.NET teams. Re-architect engineering practices into an AI-augmented model, standardizing AI-assisted development with Claude Code, Cursor, and GitHub Copilot across Dev, QA, and BA functions. Drive change management to ensure engineers adopt AI-first workflows.
Agent Architecture & Deployment: Architect agent deployment and lifecycle frameworks on Vertex AI with Claude and Gemini Enterprise as primary models. Establish reusable agent patterns including RAG pipelines, tool/function calling, MCP server integrations, and multi-step orchestration. Set standards for how agents are built, evaluated, deployed, monitored, and retired in production.
Governance & Compliance: Own AI governance for Patient Services including model selection criteria, PHI/HIPAA handling, evaluation frameworks, and approved-tools standards. Ensure every agent and AI workflow meets healthcare compliance requirements before production, coordinating with InfoSec on data-flow approval and BAA verification. Maintain the AI risk register and prompt/pattern library governance.
Delivery Leadership: Lead a hybrid onshore/offshore team on a follow-the-sun model with architecture and stakeholder alignment during US hours and offshore execution overnight. Plan parallel-track delivery for multiple AI MVPs and tech workstreams. Define AI velocity KPIs and report quarterly progress and ROI to the CTO and CFO.
Stakeholder Interface: Serve as the senior technical voice for AI in Patient Services with the CTO, CFO, Enterprise AI leadership, and external vendor partners. Coordinate with adjacent pods and existing product teams.
Required qualifications: 8+ years in software engineering with 3+ years in a technical lead or architect capacity. Demonstrated experience architecting and deploying LLM-based systems or AI agents in production. Hands-on fluency with a major cloud AI platform (Vertex AI preferred; AWS Bedrock or Azure OpenAI acceptable) and leading LLMs (Claude, Gemini, or equivalent). Working knowledge of agent design patterns.
