
This role is responsible for architecting and implementing the Agentic capabilities of the PHI ecosystem. The engineer will lead the development of multi-agent systems, enabling seamless interoperability between AI agents, internal tools, and external services.
The position requires a strong focus on AI safety, secure agent orchestration, and tool-connected AI systems capable of executing complex workflows within the health insurance domain.
1. Agent Orchestration
- Build and manage autonomous AI agents using Agent Development Kit (ADK) and Vertex AI Agent Engine.
- Design and implement multi-agent workflows capable of handling complex tasks.
2. Interoperability
- Implement the Model Context Protocol (MCP) to enable connectivity between:
- AI agents
- Internal PHI tools
- External services and APIs.
3. Multimodal Development
- Build real-time, bidirectional audio applications using the Gemini Live API.
- Integrate image generation models and support multimodal AI capabilities.
4. Safety Engineering
- Implement AI safety layers to protect sensitive healthcare data.
- Use Model Armor and Cloud DLP API to:
- Sanitize prompts
- Prevent exposure of PII/PHI data
- Enforce secure AI interactions.
5. Agent-to-Agent (A2A) Communication
- Configure remote agent connectivity using the A2A SDK.
- Enable cross-agent collaboration and workflow orchestration.
Must-Have Skills
- Advanced proficiency with Agent Development Kit (ADK).
- Strong experience with Vertex AI Agent Engine.
- Hands-on experience with Model Context Protocol (MCP).
- Experience implementing Agent-to-Agent (A2A) workflows using the A2A SDK.
- Expertise in Google Gen AI SDK for Python.
- Experience building multimodal AI applications.
- Proven experience implementing AI safety layers, including:
- Model Armor
- Cloud DLP API
Good-to-Have Skills (Foundation)
Data & Analytics
- BigQuery optimization techniques, including:
- Partitioning
- Clustering
- Denormalization for performance and cost optimization.
Streaming & Real-Time Pipelines
- Experience building real-time data pipelines using:
- Google Pub/Sub
- BigQuery streaming pipelines

About Quantiphi
About
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to reimagine and realize transformational opportunities at the heart of the business. Since its inception in 2013, Quantiphi has solved the toughest and most complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve accelerated and quantifiable business results.
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Bengaluru, Mumbai, and Trivandrum
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