Custom Application Architect

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