Shift Timing: 1.30PM - 10.30PM IST (UK Shift Time)
About the Role: We are hiring an AI / GenAI Engineer to build and deploy production agents on Google Vertex AI (now the Gemini Enterprise Agent Platform). You will work end-to-end from prototyping with Gemini models and RAG to building multi-agent workflows with the Agent Development Kit (ADK) to deploying on Agent Runtime with proper governance evaluation and monitoring. This is a hands-on engineering role with direct client and solution-design exposure.
Key Responsibilities:
Design build and deploy enterprise-grade AI agents on Vertex AI / Gemini Enterprise Agent Platform (Model Garden Agent Builder / Agent Studio Agent Engine / Agent Runtime Vertex AI Pipelines Model Registry Endpoints).
Develop GenAI applications using Gemini (3.x family) and other Model Garden models prompt engineering function calling structured output and model evaluation/tuning.
Build RAG pipelines using Vertex AI Search Vector Search RAG Engine and embeddings; implement grounding against enterprise data sources.
Implement multi-agent orchestration using the Agent Development Kit (ADK) Memory Bank / Sessions and the Agent2Agent (A2A) protocol; integrate tools via Model Context Protocol (MCP) servers.
Productionize models and agents with solid MLOps practices: CI/CD Vertex AI Pipelines model/agent monitoring observability and cost optimization.
Integrate AI services with enterprise systems and APIs (REST/gRPC FastAPI) and wider GCP services (BigQuery Cloud Run Cloud Functions Pub/Sub GCS Dataflow GKE).
Apply enterprise governance and security IAM data privacy and responsible-AI guardrails.
Partner with solution architects and client stakeholders to gather requirements design solutions and document deliverables.
Required Skills & Qualifications:
48 years of software/ML engineering experience with hands-on Vertex AI / Gemini Enterprise Agent Platform (or equivalent GCP AI) project experience.
Practical experience building GenAI / LLM applications prompting RAG embeddings vector databases and model evaluation.
Working knowledge of Google Cloud Platform core services (BigQuery Cloud Run/Functions GCS IAM Pub/Sub).
Experience deploying and operating models/agents in production (MLOps containerization with Docker basic Kubernetes/GKE).
Solid understanding of agentic AI concepts tool use multi-agent orchestration memory and agent governance.
Strong API design and integration skills (REST/gRPC FastAPI).
Good communication and the ability to work directly with clients and cross-functional teams.
Good-to-Have (Preferred):
Google Cloud certification Professional Machine Learning Engineer or Professional Cloud Architect.
Experience with the Agent Development Kit (ADK) A2A protocol and MCP integrations.
Familiarity with orchestration frameworks such as LangGraph LangChain or LlamaIndex.
Exposure to other AI stacks (AWS Bedrock Azure OpenAI Anthropic Claude) for multi-cloud / multi-model work.
Experience integrating AI with enterprise platforms (NetSuite Salesforce ERP/CRM systems).
Background in consulting / client-facing delivery environments.
Education:
Bachelors or Masters degree in Computer Science Engineering Data Science or a related field (B.E. / / M.E. / / MCA). Equivalent practical experience also considered.
Required Skills:
Position: AI/Gen AI Engineer Location: Chennai - Onsite/Hybrid/Remote Engagement Type: Full Time Shift Timing: 1.30PM - 10.30PM IST (UK Shift Time) About the Role: We are hiring an AI / GenAI Engineer to build and deploy production agents on Google Vertex AI (now the Gemini Enterprise Agent Platform). You will work end-to-end from prototyping with Gemini models and RAG to building multi-agent workflows with the Agent Development Kit (ADK) to deploying on Agent Runtime with proper governance evaluation and monitoring. This is a hands-on engineering role with direct client and solution-design exposure. Key Responsibilities: Design build and deploy enterprise-grade AI agents on Vertex AI / Gemini Enterprise Agent Platform (Model Garden Agent Builder / Agent Studio Agent Engine / Agent Runtime Vertex AI Pipelines Model Registry Endpoints). Develop GenAI applications using Gemini (3.x family) and other Model Garden models prompt engineering function calling structured output and model evaluation/tuning. Build RAG pipelines using Vertex AI Search Vector Search RAG Engine and embeddings; implement grounding against enterprise data sources. Implement multi-agent orchestration using the Agent Development Kit (ADK) Memory Bank / Sessions and the Agent2Agent (A2A) protocol; integrate tools via Model Context Protocol (MCP) servers. Productionize models and agents with solid MLOps practices: CI/CD Vertex AI Pipelines model/agent monitoring observability and cost optimization. Integrate AI services with enterprise systems and APIs (REST/gRPC FastAPI) and wider GCP services (BigQuery Cloud Run Cloud Functions Pub/Sub GCS Dataflow GKE). Apply enterprise governance and security IAM data privacy and responsible-AI guardrails. Partner with solution architects and client stakeholders to gather requirements design solutions and document deliverables. Required Skills & Qualifications: 48 years of software/ML engineering experience with hands-on Vertex AI / Gemini Enterprise Agent Platform (or equivalent GCP AI) project experience. Strong Python programming; clean production-quality code. Practical experience building GenAI / LLM applications prompting RAG embeddings vector databases and model evaluation. Working knowledge of Google Cloud Platform core services (BigQuery Cloud Run/Functions GCS IAM Pub/Sub). Experience deploying and operating models/agents in production (MLOps containerization with Docker basic Kubernetes/GKE). Solid understanding of agentic AI concepts tool use multi-agent orchestration memory and agent governance. Strong API design and integration skills (REST/gRPC FastAPI). Good communication and the ability to work directly with clients and cross-functional teams. Good-to-Have (Preferred): Google Cloud certification Professional Machine Learning Engineer or Professional Cloud Architect. Experience with the Agent Development Kit (ADK) A2A protocol and MCP integrations. Familiarity with orchestration frameworks such as LangGraph LangChain or LlamaIndex. Exposure to other AI stacks (AWS Bedrock Azure OpenAI Anthropic Claude) for multi-cloud / multi-model work. Experience integrating AI with enterprise platforms (NetSuite Salesforce ERP/CRM systems). Background in consulting / client-facing delivery environments. Education: Bachelors or Masters degree in Computer Science Engineering Data Science or a related field (B.E. / / M.E. / / MCA). Equivalent practical experience also considered.
Required Education:
Any Degree
Position: AI/Gen AI EngineerLocation: Chennai - Onsite/Hybrid/RemoteEngagement Type: Full TimeShift Timing: 1.30PM - 10.30PM IST (UK Shift Time)About the Role: We are hiring an AI / GenAI Engineer to build and deploy production agents on Google Vertex AI (now the Gemini Enterprise Agent Platform). Y...
Position: AI/Gen AI Engineer
Location: Chennai - Onsite/Hybrid/Remote
Engagement Type: Full Time
Shift Timing: 1.30PM - 10.30PM IST (UK Shift Time)
About the Role: We are hiring an AI / GenAI Engineer to build and deploy production agents on Google Vertex AI (now the Gemini Enterprise Agent Platform). You will work end-to-end from prototyping with Gemini models and RAG to building multi-agent workflows with the Agent Development Kit (ADK) to deploying on Agent Runtime with proper governance evaluation and monitoring. This is a hands-on engineering role with direct client and solution-design exposure.
Key Responsibilities:
Design build and deploy enterprise-grade AI agents on Vertex AI / Gemini Enterprise Agent Platform (Model Garden Agent Builder / Agent Studio Agent Engine / Agent Runtime Vertex AI Pipelines Model Registry Endpoints).
Develop GenAI applications using Gemini (3.x family) and other Model Garden models prompt engineering function calling structured output and model evaluation/tuning.
Build RAG pipelines using Vertex AI Search Vector Search RAG Engine and embeddings; implement grounding against enterprise data sources.
Implement multi-agent orchestration using the Agent Development Kit (ADK) Memory Bank / Sessions and the Agent2Agent (A2A) protocol; integrate tools via Model Context Protocol (MCP) servers.
Productionize models and agents with solid MLOps practices: CI/CD Vertex AI Pipelines model/agent monitoring observability and cost optimization.
Integrate AI services with enterprise systems and APIs (REST/gRPC FastAPI) and wider GCP services (BigQuery Cloud Run Cloud Functions Pub/Sub GCS Dataflow GKE).
Apply enterprise governance and security IAM data privacy and responsible-AI guardrails.
Partner with solution architects and client stakeholders to gather requirements design solutions and document deliverables.
Required Skills & Qualifications:
48 years of software/ML engineering experience with hands-on Vertex AI / Gemini Enterprise Agent Platform (or equivalent GCP AI) project experience.
Practical experience building GenAI / LLM applications prompting RAG embeddings vector databases and model evaluation.
Working knowledge of Google Cloud Platform core services (BigQuery Cloud Run/Functions GCS IAM Pub/Sub).
Experience deploying and operating models/agents in production (MLOps containerization with Docker basic Kubernetes/GKE).
Solid understanding of agentic AI concepts tool use multi-agent orchestration memory and agent governance.
Strong API design and integration skills (REST/gRPC FastAPI).
Good communication and the ability to work directly with clients and cross-functional teams.
Good-to-Have (Preferred):
Google Cloud certification Professional Machine Learning Engineer or Professional Cloud Architect.
Experience with the Agent Development Kit (ADK) A2A protocol and MCP integrations.
Familiarity with orchestration frameworks such as LangGraph LangChain or LlamaIndex.
Exposure to other AI stacks (AWS Bedrock Azure OpenAI Anthropic Claude) for multi-cloud / multi-model work.
Experience integrating AI with enterprise platforms (NetSuite Salesforce ERP/CRM systems).
Background in consulting / client-facing delivery environments.
Education:
Bachelors or Masters degree in Computer Science Engineering Data Science or a related field (B.E. / / M.E. / / MCA). Equivalent practical experience also considered.
Required Skills:
Position: AI/Gen AI Engineer Location: Chennai - Onsite/Hybrid/Remote Engagement Type: Full Time Shift Timing: 1.30PM - 10.30PM IST (UK Shift Time) About the Role: We are hiring an AI / GenAI Engineer to build and deploy production agents on Google Vertex AI (now the Gemini Enterprise Agent Platform). You will work end-to-end from prototyping with Gemini models and RAG to building multi-agent workflows with the Agent Development Kit (ADK) to deploying on Agent Runtime with proper governance evaluation and monitoring. This is a hands-on engineering role with direct client and solution-design exposure. Key Responsibilities: Design build and deploy enterprise-grade AI agents on Vertex AI / Gemini Enterprise Agent Platform (Model Garden Agent Builder / Agent Studio Agent Engine / Agent Runtime Vertex AI Pipelines Model Registry Endpoints). Develop GenAI applications using Gemini (3.x family) and other Model Garden models prompt engineering function calling structured output and model evaluation/tuning. Build RAG pipelines using Vertex AI Search Vector Search RAG Engine and embeddings; implement grounding against enterprise data sources. Implement multi-agent orchestration using the Agent Development Kit (ADK) Memory Bank / Sessions and the Agent2Agent (A2A) protocol; integrate tools via Model Context Protocol (MCP) servers. Productionize models and agents with solid MLOps practices: CI/CD Vertex AI Pipelines model/agent monitoring observability and cost optimization. Integrate AI services with enterprise systems and APIs (REST/gRPC FastAPI) and wider GCP services (BigQuery Cloud Run Cloud Functions Pub/Sub GCS Dataflow GKE). Apply enterprise governance and security IAM data privacy and responsible-AI guardrails. Partner with solution architects and client stakeholders to gather requirements design solutions and document deliverables. Required Skills & Qualifications: 48 years of software/ML engineering experience with hands-on Vertex AI / Gemini Enterprise Agent Platform (or equivalent GCP AI) project experience. Strong Python programming; clean production-quality code. Practical experience building GenAI / LLM applications prompting RAG embeddings vector databases and model evaluation. Working knowledge of Google Cloud Platform core services (BigQuery Cloud Run/Functions GCS IAM Pub/Sub). Experience deploying and operating models/agents in production (MLOps containerization with Docker basic Kubernetes/GKE). Solid understanding of agentic AI concepts tool use multi-agent orchestration memory and agent governance. Strong API design and integration skills (REST/gRPC FastAPI). Good communication and the ability to work directly with clients and cross-functional teams. Good-to-Have (Preferred): Google Cloud certification Professional Machine Learning Engineer or Professional Cloud Architect. Experience with the Agent Development Kit (ADK) A2A protocol and MCP integrations. Familiarity with orchestration frameworks such as LangGraph LangChain or LlamaIndex. Exposure to other AI stacks (AWS Bedrock Azure OpenAI Anthropic Claude) for multi-cloud / multi-model work. Experience integrating AI with enterprise platforms (NetSuite Salesforce ERP/CRM systems). Background in consulting / client-facing delivery environments. Education: Bachelors or Masters degree in Computer Science Engineering Data Science or a related field (B.E. / / M.E. / / MCA). Equivalent practical experience also considered.
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