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Senior AI Engineer - Agentic AI & Multi-Agent Systems (Google Cloud)

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Onsite

Senior AI Engineer - Agentic AI & Multi-Agent Systems (Google Cloud)

Tata Consultancy Services

Senior AI Engineer - Agentic AI & Multi-Agent Systems (Google Cloud)

Skills

Google Cloud PlatformDockerPythonGoogle BigQueryMachine LearningAIKubernetesGDPRTerraform

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

21 August 2026

What they need


Role & responsibilities

We are seeking an experienced Senior AI Engineer with expertise in Agentic AI, Multi-Agent Systems, ADK, Vertex AI, Gemini, and Generative AI solutions. The ideal candidate will lead the design, development, deployment, and optimization of enterprise-scale AI applications on Google Cloud Platform, leveraging modern AI frameworks, RAG architectures, and advanced agent orchestration techniques to solve complex business challenges.

Preferred candidate profile

  • 6 to 8 years of experience in Software Engineering, AI Engineering, Machine Learning, or Cloud-based application development.
  • Hands-on experience designing and implementing Agentic AI and Multi-Agent Systems using ADK, Vertex AI Agent Builder, Agent Engine, MCP, and A2A frameworks.
  • Strong expertise in Generative AI, LLMs, Gemini, Prompt Engineering, RAG, Embeddings, Vector Search, and Vector Databases.
  • Advanced proficiency in Python, Fast API, REST API including Vertex AI, Big Query, Cloud Storage, IAM, Cloud Run, GKE, and Secret Manager.
  • Strong experience with Google Cloud Platform (GCP) including Vertex AI, BigQuery, Cloud Storage, IAM, Cloud Run, GKE, and Secret Manager.
  • Experience in designing scalable, secure, and prod including Vertex AI, Big Query, Cloud Storage, IAM, Cloud Run, GKE, and Secret Manager.
  • Strong understanding of AI Security, Responsible AI, Governance, IAM, Data Protection, Guardrails, and Prompt Injection Prevention.
  • Experience implementing LLM Ops, ML Ops, CI/CD, Docker, Kubernetes, Terraform, Monitoring, and Observability practices.
  • Expertise in AI evaluation frameworks covering hallucination detection, grounded ness, retrieval quality, latency, cost optimization, and agent performance.
  • Experience integrating AI solutions with enterprise applications, databases, APIs, SaaS platforms, and business workflo
  • Excellent stakeholder management, problem-solving, architecture design, and communication

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