• 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 BigQuery or other datastores 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.

Required Technical Skills

• Core AI: Deep proficiency with LangChain or LangGraph, 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 BigQuery; 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.

Qualifications

• Experience:
• 5+ years of software development experience.
• 2+ years of hands-on experience building and deploying enterprise-grade agentic applications (e.g., using LangGraph, LangChain Agents).
• Familiarity with scalable, enterprise-level distributed systems
• Experience with advanced data structures, algorithms, and complexity analysis
• Demonstrated history of product value delivery

Education:

• Bachelor's degree in Computer Science, Computer Engineering, or a closely related quantitative field is required.
• Master's degree in Artificial Intelligence, Machine Learning, or a relevant field is strongly preferred.

Work Authorization:

• Must be a US Citizen, Green Card holder, or currently in the US having a valid H1B visa

Benefits Joining C the Signs is not just about building AI; it’s about shaping the future of healthcare. If you are a technical leader with an unshakable belief in the power of AI to save lives and the ability to make it happen at scale, this is your opportunity to create a tangible, global impact.

Benefits:

• Competitive salary and benefits package.
• Flexible working arrangements (remote or hybrid options available).
• The opportunity to work on life-changing AI technology that directly impacts patient outcomes.
• Join a team that combines cutting-edge innovation with a mission to save lives and improve health equity.
• Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.