Senior Machine Learning Engineer- Agentic AI

Job Title- Senior Machine Learning Engineer

Experience: 3–6 Years

Location: Mumbai / Bangalore (Hybrid)

About the Role

This role is responsible for architecting and implementing the "Agentic" c apabilities 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

%CF; Agent Orchestration: Build and manage autonomous agents using the ADK and Vertex AI Agent Engine.

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

%CF; Multimodal Development: Build real-time, bidirectional audio applications using the Gemini Live API and integrate image

generation models.

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

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

Must-Have Skills

%CF; Advanced proficiency in the Agent Development Kit (ADK) and Vertex AI Agent Engine.

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

%CF; Expertise in Google Gen AI SDK for Python and multimodal grounding.

%CF; Proven experience in implementing AI safety layers (Model Armor, Cloud DLP).

Good-to-Have Skills (Foundation)

%CF; BigQuery Optimization: Partitioning, clustering, and denormalization for cost and performance.

%CF; Stream Processing: Building real-time pipelines with Pub/Sub and BigQuery.