Senior Architect

Tata Consultancy Services; Hyderabad; On-site; INR 4,200,000 - 6,400,000; Full time

Job summary

Tata Consultancy Services in Hyderabad, Telangana, India seeks an expert to architect and deploy AI/Gen AI systems in production environments. You will design scalable, secure, high-performance Gen AI solutions focusing on LLMs, agentic AI, and MCP-driven workflows.

The role requires strong microservices, APIs, MLOps and GenAIOps skills across Azure, AWS, and Google Cloud, with leadership to mentor teams and ensure robust governance.

Qualifications

• Proven experience architecting Gen AI and AI/ML production systems.
• Design scalable, robust, secure Gen AI architectures for enterprise.
• Experience with multi-cloud (Azure, AWS, Google Cloud).
• Hands-on MLOps, CI/CD, model versioning and retraining strategies.
• Knowledge of agent-based AI with MCP, tools, memory, and orchestration.
• Strong APIs, microservices and data platform integration capabilities.

Skills

AI Architecture

Gen AI Systems

LLMs

MCP

Agentic AI

Cloud Platforms (Azure/AWS/Google)

GenAI in Enterprise

Microservices & APIs

MLOps & GenAIOps

CI/CD & Deployment

Observability & Monitoring

Job description

Notice Period : upto 3 months

Mode : Work from Office

• Proven experience in architecting and deploying AI/Gen AI systems in production environments.
• Ability to design scalable, robust, secure, and high-performance solutions with a focus on Gen AI, Large Language Models (LLMs), Agentic AI, and advanced AI technologies.
• Experience designing and architecting Agentic AI systems, including autonomous and semi-autonomous agents leveraging LLMs, Model Context Protocol (MCP), tools, workflows, memory, and orchestration frameworks.
• Strong expertise in designing enterprise-scale AI, ML, and Gen AI architectures across Azure, AWS, and Google Cloud platforms.
• Expertise in designing Gen AI solutions for enterprise use cases, including RAG, multi-agent systems, knowledge assistants, AI automation, and intelligent business workflows.
• Strong understanding of microservices, APIs, event-driven architectures, and integration with enterprise applications and data platforms.
• Strong hands-on experience with MLOps and GenAIOps practices including CI/CD, model versioning, experiment tracking, automated retraining, deployment, rollback strategies, prompt lifecycle management, and model evaluation.
• Experience implementing AI workload operations covering DevOps, DataOps, MLOps, GenAIOps, infrastructure automation, observability, monitoring, and operational governance.
• Experience in AI monitoring, model performance management, drift detection, model retraining, capacity planning, incident management, and operational support.
• Strong communication skills and the ability to collaborate effectively with architects, developers, data scientists, platform engineers, CoEs, and business stakeholders.
• Ability to mentor engineering teams and provide technical leadership throughout the solution lifecycle.