Senior AI Developer; Agentic Healthcare
Listed on 2026-02-14
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Software Development
AI Engineer, Machine Learning/ ML Engineer
Role Overview
Role Overview We are looking for a forward-thinking Senior AI Developer to architect and build the next generation of autonomous AI applications. You will move beyond standard prompt engineering to design Agentic Workflows—systems where LLMs function as reasoning engines that can plan multi-step tasks, utilize external tools (APIs, databases), and collaborate with other specialized agents to achieve high-level goals.
We are looking for a forward-thinking Senior AI Developer to architect and build the next generation of autonomous AI applications. You will move beyond standard prompt engineering to design Agentic Workflows—systems where LLMs function as reasoning engines that can plan multi-step tasks, utilize external tools (APIs, databases), and collaborate with other specialized agents to achieve high-level goals.
You will contribute to the technical implementation of "Agency" in our software, transforming passive AI responses into active, goal-oriented behaviors.
Experience working with the GCP Vertex AI ecosystem is essential. In this role, you will design agents capable of complex reasoning and tool usage, leveraging Google's managed infrastructure (Vertex AI Vector Search, Cloud Run, and Big Query) to ensure reliability, security, and performance.
Responsibilities- Architecting and Implementing Agentic Workflows
- Design Autonomous Loops:
Build stateful control loops (Perception -> Reasoning -> Action) where agents can interpret clinical data, plan necessary checks, and generate risk assessments - Conversational Agentic workflow:
Chatbot style user experience powered by LLM - GCP Integration:
Leverage Vertex AI for model serving and LLM models for reasoning, optimizing for long-context windows to process complex medical history - RAG & Grounding:
Implement "Enterprise Grounding" using Vertex AI Vector Search to ensure all agent outputs are strictly cited against official medical literature (e.g., medical research and guidelines) - Data & Tool Integration
- Structured Data Access:
Build robust Python tools (Function Calling) that allow agents to securely query Big Query or other data stores for patient demographics and symptoms - Security & Compliance:
Ensure all AI operations comply with HIPAA/GDPR standards, implementing strict PII masking and data governance within the Google Cloud environment - System Reliability:
Deploy agents on Vertex AI, Cloud Run, or GKE, ensuring low-latency inference and high availability for clinical users - Agent monitoring: implement effective product environment AI Agent execution monitoring and alert system to ensure SLA, safety and security compliance
- Leadership & Strategy
- Mentorship:
Guide a team of engineers in MLOps best practices (CI/CD for models, evaluation pipelines) - Evaluation:
Implement "LLM-as-a-Judge" frameworks to automatically test agent accuracy against "Golden Datasets" of clinical cases
- Core AI:
Deep proficiency with Lang Chain or Lang Graph, and specific experience with the Vertex AI SDK and ADK (Agent Development Kit) - Conversational workflow:
Google Dialogflow CX - LLMs:
Expertise in prompting and configuring LLMs, specifically utilizing Function Calling and Context Caching - Experience with integrating LLMs into platform and application workflow, experience with MCP protocols
- RAG/Embeddings: expert level experience in design and implementation of RAG based system using embeddings and vector databases
- Data Engineering:
Strong SQL skills for Big Query; experience with Vector Databases (Pinecone, Milvus, or Vertex Vector Search) - Backend Engineering:
Mastery of Python (FastAPI) and containerization (Docker) for deploying microservices to Cloud Run or GKE - Healthcare Domain:
Familiarity with handling unstructured medical text or clinical guidelines is highly preferred
- Experience:
- 5+ years of software development experience
- 2+ years of hands-on experience building and deploying enterprise-grade agentic applications (e.g., using Lang Graph, Lang Chain Agents)
- Familiarity with scalable, enterprise-level distributed systems
- Experience with advanced data structures, algorithms, and complexity analysis
- Demonstrated history of product value…
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