Azure AI Engineer at NTT DATA, Inc. in Bangalore, IN-KA, India

Job description

• As an Azure AI Engineer at NTT DATA in India, you will design, develop, and deploy enterprise-grade AI solutions using Microsoft Azure services. The role involves building Generative AI, Conversational AI, and intelligent automation solutions, integrating enterprise systems, and optimising AI models for performance and reliability. You will collaborate with architects, product owners, and business stakeholders to translate business requirements into scalable technical solutions. Required qualifications include a bachelor’s degree in a relevant field, at least 5 years of software engineering experience, and 2 years of hands-on AI development. Strong Python skills, experience with Azure AI services, and enterprise application integration are essential. Preferred qualifications include a master’s degree, Microsoft certifications, and experience with Copilot, Power Platform, and MLOps.
• NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.
• We are currently seeking a Azure AI Engineer to join our team in Bangalore, Karnātaka (IN-KA), India (IN).
• AI Engineer – Azure
• Location – Any Location in India
• We are seeking a highly skilled AI Engineer / AI Developer to design, develop, deploy, and optimize enterprise-grade AI solutions that deliver measurable business value. This role will work closely with AI Architects, Product Owners, Project Managers, Business Stakeholders, and Engineering teams to transform business requirements into scalable AI-powered applications and intelligent automation solutions.
• The ideal candidate possesses deep expertise in Generative AI, Large Language Models (LLMs), Agentic AI, Microsoft Azure AI services, Microsoft Copilot, Power Automate, and modern software engineering practices. They should be equally comfortable building AI solutions from concept to production, integrating enterprise systems, and optimizing AI models and platforms for performance, reliability, and cost efficiency.
• A successful candidate is a hands-on AI Engineer who can take an idea from concept to production. They possess strong expertise in Generative AI, Azure AI, Copilot, and Power Automate, while also demonstrating software engineering excellence, cloud development experience, and the ability to build secure, scalable, and production-ready AI solutions that drive business outcomes.

Responsibilities

• AI Solution Development
• Design, develop, and implement AI-powered applications using modern AI and machine learning technologies.
• Build enterprise grade Generative AI, Conversational AI, Agentic AI, and intelligent automation solutions.
• Translate business and functional requirements into scalable technical solutions.
• Collaborate with architects and business stakeholders to deliver innovative AI capabilities.
• Develop reusable frameworks, components, APIs, and accelerators to improve delivery efficiency.
• Generative AI & LLM Engineering
• Build and deploy applications leveraging Large Language Models (LLMs) and Generative AI technologies.
• Develop Retrieval Augmented Generation (RAG) solutions integrating enterprise knowledge repositories and data sources.
• Design prompt engineering strategies and conversation orchestration frameworks.
• Implement AI agents and multi-agent workflows to automate business processes and decision-making.
• Evaluate and integrate foundation models based on business requirements, performance, and cost considerations.
• Microsoft Copilot & AI Assistants
• Develop and customize Microsoft Copilot and Copilot Studio solutions.
• Build AI-powered assistants that improve employee productivity and business process efficiency.
• Integrate Copilot experiences with enterprise applications, Microsoft 365, and business workflows.
• Design knowledge grounded copilots using enterprise content and varied data sources.
• Establish best practices for Copilot adoption, security, governance, and performance optimization.
• Power Platform & Intelligent Automation
• Design and implement business process automation solutions using Power Automate.
• Build intelligent workflows integrating AI capabilities and enterprise applications.
• Develop Power Apps and AI enabled business solutions when required.
• Integrate AI services into automated workflows to improve operational efficiency.
• Create reusable automation components and accelerators.
• Azure AI & Cloud Development
• Develop AI solutions leveraging Azure AI services, Azure OpenAI, Azure AI Search, Azure Machine Learning, Azure Functions, and related cloud services.
• Build scalable APIs, microservices, and backend services supporting AI workloads.
• Implement cloud-native AI architectures that meet enterprise requirements for security, reliability, and performance.
• Configure and optimize AI infrastructure supporting solution deployment and operations.
• Collaborate with DevOps and platform teams to ensure production readiness.
• Open Source AI & Model Engineering
• Develop solutions utilizing open-source foundation models such as Llama, Mistral etc.
• Fine tune and optimize models for enterprise use cases.
• Deploy and manage model inference workloads on cloud and GPU enabled environments.
• Build model serving solutions and integrate models into enterprise systems.
• Contribute to AI platform engineering and model lifecycle management activities.
• Model Optimization & Operational Excellence
• Optimize AI applications for latency, scalability, throughput, and operational cost.
• Implement techniques such as quantization, caching, prompt optimization, and model tuning.
• Monitor application performance and continuously improve model effectiveness.
• Support evaluation, testing, and validation frameworks for AI solutions.
• Ensure adherence to Responsible AI, security, and compliance requirements.
• Collaboration & Technical Leadership
• Collaborate with cross-functional teams including Architects, Product Managers, Data Scientists, Developers, and Business Stakeholders.
• Participate in architecture reviews, code reviews, and technical design discussions.
• Mentor junior engineers and contribute to AI engineering best practices.
• Stay current with emerging AI technologies, frameworks, and industry trends.
• Support client engagements, solution demonstrations, and technical workshops when required.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Technology, Data Science, or a related field.
• 5+ years of software engineering or application development experience.
• 2+ years of hands-on experience designing and developing AI, Machine Learning, or Generative AI solutions.
• Strong development experience with Python and modern software engineering practices.
• Hands-on experience with Azure AI services and cloud-native application development.
• Experience building enterprise applications integrating LLMs and Generative AI capabilities.
• Experience with API development, microservices, and enterprise system integration.
• Strong problem-solving, communication, and stakeholder engagement skills.
• Master's degree in Artificial Intelligence, Computer Science, Data Science, or a related discipline.
• Microsoft certifications in Azure AI, Power Platform, or related technologies.
• Experience developing Microsoft Copilot and Copilot Studio solutions.
• Experience building Power Automate and Power Platform solutions.
• Experience with MLOps, LLMOps, CI/CD, and AI deployment pipelines.
• Experience deploying AI workloads in Kubernetes and containerized environments.
• Experience working with enterprise scale AI transformation programs.

Skills

Required

• Python
• Azure AI services
• Cloud-native application development
• API development
• Microservices
• Enterprise system integration
• LLMs and Generative AI
• Problem-solving
• Communication
• Stakeholder engagement

Preferred

• Microsoft Copilot
• Copilot Studio
• Power Automate
• Power Platform
• MLOps
• LLMOps
• CI/CD
• AI deployment pipelines