Description:
- Architect end to end GenAI and Agentic AI solutions using Google Cloud Platform GCP including Vertex AI APIs and Agent Development Kit ADK
- Design multiagent architectures supporting Agent to Agent A2A communication orchestration and collaboration across diverse enterprise functions
- Define LLM solution strategy model selection finetuning grounding and retrieval augmented generation RAG pipelines for contextual accuracy
- Establish context and memory engineering frameworks embedding stores vector databases and persistence strategies
- Architect prompt management and function calling layers for seamless integration between agents APIs and enterprise business logic
- Oversee ML and data architecture data pipelines model lifecycle management and operationalization
- Design API and microservice integration patterns to enable secure low latency communication among agents backend systems and UIUX layers
- Implement governance observability and compliance frameworks for GenAI deployments ensuring alignment with enterprise data security and regulatory standards
- Evaluate and recommend emerging Agentic AI frameworks LLMOps tools and GCP native innovations Gemini ADK Agent Builder for continuous architecture evolution
- Collaborate with Data Engineers AI Engineers and Product teams to translate business requirements into scalable AI blueprints and ensure seamless delivery across agentic ecosystems
- Experience with banking related AI GenAI use cases will be a plus
Skills
Mandatory Skills : Application Architecture
Good to Have Skills : LangChain, Amazon Bedrock, Architecture Patterns and Styles, Generative AI/Open AI/Vector DB