AI Architect

T-Systems Information and Communication Technology India Private Limited (T-Systems ICT India Pvt. Ltd.) is a proud recipient of the prestigious Great Place To Work® Certification™. As a wholly owned subsidiary of T-Systems International GmbH, T-Systems India operates across Pune, Bangalore, and Nagpur, boasting a dedicated team of 3500+ employees providing services to group customers. T-Systems offers integrated end-to-end IT solutions, driving the digital transformation of companies in all industries, including automotive, manufacturing, logistics, and transportation, as well as healthcare and the public sector. T-Systems develops vertical, company-specific software solutions for these sectors. T-Systems International GmbH is an information technology and digital transformation company with a presence in over 20 countries and a revenue of more than €4 billion. T-Systems is a world-leading provider of digital services and has over 20 years of experience in the transformation and management of IT systems. As a subsidiary of Deutsche Telekom and a market leader in Germany, T-Systems International offers secure, integrated information technology and digital solutions from a single source.

Job Summary:

1. We are seeking a visionary AI Architect to lead the design, development, and deployment of advanced AI systems, including MCP (Multi-Component Platform) server and client infrastructure, chat orchestration frameworks, and cutting-edge agentic AI solutions with Data Governance.

2. This role requires deep expertise in AI system architecture, multi-agent coordination, and scalable infrastructure to enable next-generation intelligent applications. 

Key Responsibilities:

1.Architect and lead the development of agentic AI Chat systems that autonomously perform tasks and show relevant results to questions asked. 

2.Design and develop MCP server and client architectures ensuring high performance, scalability, and reliability.

3.Architect and implement advanced chat orchestration systems to enable seamless multi-turn conversations with context-awareness and dynamic intent handling.

4.Utilize Azure Stack services including Azure Machine Learning, Azure Cognitive Services, and Azure Kubernetes Service for deploying and scaling AI models.

5.Lead the design and development of agentic AI models, enabling autonomous decision-making agents that can collaborate, negotiate, and adapt to changing environments.

6.Develop frameworks and protocols for multi-agent AI coordination and communication to support complex workflows and emergent behaviors.

7.Collaborate with cross-functional teams including data scientists, ML engineers, Data Engineers, and product managers to integrate AI solutions into production systems.

8.Define technical roadmaps, architectural standards, and best practices for AI system development.

9.Evaluate new AI technologies and frameworks to continuously enhance system capabilities.

10.Ensure system security, data privacy, and compliance with relevant regulations.

11.Troubleshoot and optimize AI models and infrastructure for latency, throughput, and resource efficiency. _

Required Qualifications:

1. Proven experience as an AI Architect or similar role designing large-scale AI/ML systems.

2.Strong expertise in AI/ML frameworks (TensorFlow, PyTorch, etc.) and programming languages (Python).

3. Deep understanding of multi-agent systems, agentic AI principles, and chat orchestration methodologies. 4. Experience with building and deploying scalable backend services (MCP server/client) and distributed systems.

5.Familiarity with NLP, conversational AI, dialogue management, and context-aware AI systems.

6.Solid knowledge of cloud platforms (Azure) and container orchestration (Kubernetes, Docker).

7.Strong skills in system design, microservices architecture, and API development.

8.Excellent problem-solving, communication, and leadership skills.

Preferred Skills: 

1.Experience with reinforcement learning, meta-learning, or adaptive AI techniques.

2.Familiarity with AI ethics, bias mitigation, and privacy-preserving AI methods.

3.Knowledge of event-driven architecture and real-time data processing.

4.Exposure to DevOps practices and CI/CD pipelines for AI applications.

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