Job description
Project Role : Custom Application Architect
Project Role Description : Provide functional and/or technical expertise to plan, analyze, define and support the delivery of future functional and technical capabilities for an application or group of applications. Assist in facilitating impact assessment efforts and in producing and reviewing estimates for client work requests.
Must have skills : Google Cloud Platform Architecture
Good to have skills : Contact Center Technology Capabilities, Contact Center Technology Implementation, Python (Programming Language)
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary
As a GenAI & Agent Development Lead, you will be responsible for developing and delivering agent-based AI applications and platforms using Google Agent Development Kit (ADK) and Google Cloud AI services. Your typical day will involve applying Generative AI models (Gemini), RAG-based retrieval, and agent orchestration patterns to build intelligent, scalable, and production-ready AI solutions.
You should have strong hands-on experience in designing, building, deploying, and optimizing AI agents, with a growing ability to guide teams and contribute to solution design.
Roles & Responsibilities
Solutioning and designing agent-based GenAI applications and systems using Google ADK and Vertex AI
Design, develop, and maintain AI agents and agent workflows, including single-agent and multi-agent patterns and Agent-to-Agent (A2A) communication flows
Implement MCP-based orchestration concepts for agent execution, control, and coordination
Build RAG pipelines, including data ingestion, chunking strategies, embedding generation, and retrieval optimization
Contribute to Graph RAG implementations, leveraging knowledge graphs for enhanced reasoning and context
Implement Gemini Enterprise–based solutions, grounding models on first-party (1P) enterprise data and third-party (3P) systems and data sources
Apply Vertex AI Machine Learning services for embeddings, inference, evaluation, and pipelines
Integrate agents with enterprise systems, APIs, tools, and workflows
Apply prompt engineering techniques, including role prompting and prompt chaining
Assist in implementing agent observability, including logging, tracing, and quality monitoring
Follow secure agent design practices, including controlled tool access and safe execution
Document technical designs, agent workflows, and deployment setups
Provide technical guidance to L9/L10 team members and support Manager in delivery execution
Professional & Technical Skills
Must Have Skills
Hands-on experience with Google Agent Development Kit (ADK)
Strong understanding of Generative AI and Gemini models
Experience with RAG architectures and chunking strategies
Working knowledge of Agent-to-Agent (A2A) patterns
Familiarity with MCP or similar agent orchestration concepts
Experience with Vertex AI Machine Learning services
Prompt engineering and agent workflow design
Strong programming skills in Python (or Node.js)
Good To Have Skills
Knowledge of Graph RAG / Knowledge Graph integration
Cloud data architecture on Google Cloud
Google Cloud certifications (Google Cloud Machine Learning Services / Cloud Architect)
Experience with enterprise-grade CI/CD and production pipelines
Additional Information
10+ years of relevant experience
Proficient in Google Cloud Machine Learning Services, GenAI, and agent-based systems
Strong foundation in computer science, AI/ML, or related fields
This job post has been translated by AI and may contain minor differences or errors.
