Machine Learning Engineer (Gen AI)

About the Role

This role is responsible for architecting and implementing the Agentic capabilities of the PHI ecosystem. You will lead the development of multi-agent interactions and ensure technical interoperability through advanced protocols. The role requires a strong focus on AI safety and the implementation of secure, tool-connected agents that can execute complex tasks within the health insurance domain.

Key Responsibilities

● Agent Orchestration: Build and manage autonomous agents using the ADK and Vertex AI Agent Engine.

● Interoperability: Implement the Model Context Protocol (MCP) to connect AI agents with internal PHI tools and external services.

● Multimodal Development: Build real-time, bidirectional audio applications using the Gemini Live API and integrate image generation models.

● Safety Engineering: Implement Model Armor and the Cloud DLP API to sanitize prompts and protect sensitive health data (PII/PHI).

● Agent-to-Agent (A2A): Configure remote agent connectivity using the A2A SDK for cross-functional workflows.

Must-Have Skills

● 3 to 7 years of experience in Machine Learning/Data Science domain.

● Advanced proficiency in the Agent Development Kit (ADK) and Vertex AI Agent Engine.

● Hands-on experience with MCP (Model Context Protocol) and the A2A SDK.

● Expertise in Google Gen AI SDK for Python and multimodal grounding.

● Proven experience in implementing AI safety layers (Model Armor, Cloud DLP). Good-to-Have Skills (Foundation)

● BigQuery Optimization: Partitioning, clustering, and denormalization for cost and performance.

● Stream Processing: Building real-time pipelines with Pub/Sub and Big Query