Role & responsibilities
- Develop and deploy Gen AI, Agentic AI, Multi-Agent Systems, and RAG solutions on GCP.
- Build AI applications using Vertex AI, Gemini, Python, Fast API, and cloud-native services.
- Design scalable AI architectures and enterprise integrations.
- Implement prompt engineering, vector search, embeddings, and model evaluation.
- Manage AI deployment, ML Ops, CI/CD, monitoring, and production support.
- Ensure security, governance, Responsible AI, and performance optimization.
- Collaborate with stakeholders to deliver innovative AI-driven business solutions.

Preferred candidate profile
- Expertise in GCP, Vertex AI, Gemini Enterprise, Generative AI, and Agentic AI.
- Hands-on experience in Multi-Agent Systems,



RAG Pipeline Development, Prompt Engineering, LLMs, and Vector Databases.
- Strong proficiency in Python, Rapid API, Docker, Kubernetes, Terraform, and CI/CD.
- Experience designing scalable enterprise AI solutions and deploying production-grade AI applications on Google Cloud.
- Excellent communication, stakeholder management, and solution design capabilities.
- Google Cloud certifications such as Professional Cloud Architect or Professional Machine Learning Engineer are highly desirable

📌 AI Engineer | Gen AI, Agentic AI, Gemini, GCP (India)
🏢 Tata Consultancy Services
📍 India