Back
Remote, mid-level AI role with broad LLM and integration requirements increases applicant density significantly.
Core LLM, RAG, and cloud AI skills transfer well across industries though healthcare integrations increase sensitivity.
Multiple mandatory technical requirements (Vertex, RAG, embeddings, Salesforce/MuleSoft) enforce stringent filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Build and productionize AI agents and workflows on enterprise AI stack (GCP, Vertex AI, Claude, Gemini Enterprise) for Patient Services use cases such as intake automation and adverse-event detection.
Develop and maintain RAG pipelines, vector stores, and AI integrations with Salesforce Health Cloud, MuleSoft, and Java SDLC touchpoints.
Own the full agent lifecycle including deployment, evaluation against quality standards, monitoring for drift/cost/latency, and remediation.
5+ years of software engineering experience with production systems.
Advanced Python skills; competence in JavaScript/TypeScript.
Experience with cloud AI platforms, preferably Vertex AI, and SDKs.
Practical experience with RAG, vector databases, embeddings, prompt engineering, LLMs (Claude, Gemini, or equivalent), and AI agent orchestration frameworks.
Experienced in integrating AI solutions within healthcare or regulated environments, familiar with PHI/HIPAA constraints preferred but not mandatory.
Proficient in API integrations and Salesforce/MuleSoft development to embed AI workflows in production environments.
Able to implement reusable AI agent patterns and monitoring frameworks, supporting scalable enterprise AI adoption.