Senior AI Solution Architect - Specialist Advisor at NTT DATA
Bengaluru, karnataka, India -
Full Time


Start Date

Immediate

Expiry Date

17 Feb, 26

Salary

0.0

Posted On

19 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

AI, ML, Generative AI, LLM Integration, Python, NLP, ML Frameworks, Cloud Deployment, ML System Architecture, Agentic AI, AutoGen, Semantic Kernel, Model Governance, Team Leadership, GPU Optimization, Ethical AI

Industry

IT Services and IT Consulting

Description
- Architect and deploy GenAI applications using Azure, AWS, or GCP. - Leverage cutting-edge LLMs, Microsoft Semantic Kernel, and AutoGen to build intelligent single-agent and multi-agent systems for real-world business impact. - Collaborate with product, business, engineering, and data teams to solve enterprise challenges with scalable AI. - Lead technical execution, mentor engineering talent, and champion best practices in MLOps, CI/CD, and cloud AI. - Rapidly prototype solutions—think conversational orchestration, multimodal agents, RAG, and deep learning. - Deliver production-grade, compliant AI models using tools like AI Foundry and advanced frameworks. - Own documentation, process improvement, and innovation across the AI product lifecycle. What You Bring - 6-8 years in hands-on AI/ML, with 3+ years in generative AI and LLM integration (OpenAI, HuggingFace, Anthropic). - Deep Python, NLP, and ML framework experience (TensorFlow, PyTorch, LangChain). - Proven cloud deployment (Azure/AWS/GCP) and strong ML system architecture skills. - Experience designing and orchestrating agentic AI (single/multi-agent) workflows, with practical knowledge of AutoGen and Semantic Kernel. - Familiarity with Microsoft AI Foundry for model governance and lifecycle management. - Thought leadership—team mentoring, patents, publications, or conference presentations a plus. - Prior team leadership or mentoring in product-driven AI environments. - Experience with GPU/CUDA optimization and scalable deep learning. - Passion for ethical AI, compliance, and industry best practices.
Responsibilities
Architect and deploy GenAI applications using cloud platforms. Collaborate with various teams to solve enterprise challenges and lead technical execution.
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