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Remote mid-level generative-AI role with broad integration skills but niche LLM specialization limits mass competition.
Core LLM and engineering skills transfer broadly, but healthcare PHI and Salesforce/MuleSoft integrations raise domain specificity.
Multiple mandatory requirements: 5+ years, Vertex/LLM/RAG/vector DB expertise, and Salesforce/MuleSoft integrations.
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Develop and deploy production-grade AI agents and workflows on EVERSANA's enterprise AI stack (GCP, Vertex AI, Claude, Gemini) for Patient Services use cases.
Integrate AI capabilities into Salesforce Health Cloud, MuleSoft, and Java development pipelines; establish reusable prompt templates and agent patterns.
Manage full agent lifecycle: build, deploy, monitor, evaluate (quality bars), and retire; maintain evaluation and monitoring practices for production agents.
5+ years in software engineering with experience building production systems.
Proficiency in advanced Python; competent in JavaScript/TypeScript.
Experience with cloud AI platforms (Vertex AI preferred), prompt engineering, LLM application development (Claude, Gemini, or equivalent).
Practical working knowledge of RAG, vector databases, embeddings, agent orchestration frameworks, REST/GraphQL APIs; Salesforce and/or MuleSoft integration experience is a strong plus.
Hands-on engineer with deep experience building real AI systems in regulated healthcare environments focused on Patient Services workflows.
Experienced in integrating AI tooling within enterprise SDLC environments including Salesforce, MuleSoft, and Java.
Able to operationalize AI agents end-to-end including designing evaluation frameworks and maintaining deployed agents for performance and compliance.