Senior Technical Lead
- India
Posted yesterday
About the role
Bengaluru, Karnataka
Job Summary
Designs and builds enterprise-grade AI agents on Google Gemini Enterprise using the Agent Development Kit (ADK) for Intel's Finance, Marketing, and HR use cases. Implements agent logic, orchestration, memory, tools, prompts, and guardrails, and contributes reusable components to the Intel Agent Library.
Key Responsibilities
Develop AI agents using Google ADK, Gemini foundation models, and the A2A protocol.
Implement agent reasoning, planning, tool invocation, memory, and sub-agent orchestration.
Integrate agents with enterprise data (Databricks, ServiceNow, Snowflake, OneDrive, Adobe, PDFs) via MCP and RAG.
Build reusable, modular agent components and publish to the Intel Agent Library.
Perform unit and evaluation testing using the ADK eval framework; optimize prompts and model configuration.
Collaborate with Data & AI Engineers, API/MCP Developers, and FDEs across the sprint lifecycle.
Skill Requirements
Hands-on Google ADK and Gemini Enterprise agent development.
Strong Python and prompt engineering for LLM/GenAI applications.
Experience with RAG, embeddings, vector search, and grounding.
Understanding of agent orchestration (A2A) and MCP tool integration.
Other Requirements
Vertex AI, LangChain / LlamaIndex, Cloud Run / GKE.
AI safety, evaluation, and guardrail patterns (Model Armor, Guardrails AI).
Finance / Marketing / HR domain exposure.
6+ years software engineering with 2+ years GenAI/LLM development.
Google Cloud / Gemini / ADK certification preferred.
Must be able to work onsite in the USA aligned to Intel hours.
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Job Summary
Designs and builds enterprise-grade AI agents on Google Gemini Enterprise using the Agent Development Kit (ADK) for Intel's Finance, Marketing, and HR use cases. Implements agent logic, orchestration, memory, tools, prompts, and guardrails, and contributes reusable components to the Intel Agent Library.
Key Responsibilities
Develop AI agents using Google ADK, Gemini foundation models, and the A2A protocol.
Implement agent reasoning, planning, tool invocation, memory, and sub-agent orchestration.
Integrate agents with enterprise data (Databricks, ServiceNow, Snowflake, OneDrive, Adobe, PDFs) via MCP and RAG.
Build reusable, modular agent components and publish to the Intel Agent Library.
Perform unit and evaluation testing using the ADK eval framework; optimize prompts and model configuration.
Collaborate with Data & AI Engineers, API/MCP Developers, and FDEs across the sprint lifecycle.
Skill Requirements
Hands-on Google ADK and Gemini Enterprise agent development.
Strong Python and prompt engineering for LLM/GenAI applications.
Experience with RAG, embeddings, vector search, and grounding.
Understanding of agent orchestration (A2A) and MCP tool integration.
Other Requirements
Vertex AI, LangChain / LlamaIndex, Cloud Run / GKE.
AI safety, evaluation, and guardrail patterns (Model Armor, Guardrails AI).
Finance / Marketing / HR domain exposure.
6+ years software engineering with 2+ years GenAI/LLM development.
Google Cloud / Gemini / ADK certification preferred.
Must be able to work onsite in the USA aligned to Intel hours.
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