AI Infrastructure Engineer

About LTIMindtree LTIMindtree is a global technology consulting and digital solutions company that enables enterprises to reimagine business models and accelerate innovation through digital technologies. Powered by more than 84,000 entrepreneurial professionals across more than 30 countries, LTIMindtree caters to over 700 clients. We are a Larsen & Toubro Group company with the combined strength of erstwhile Larsen and Toubro Infotech and Mindtree. Client : LTIMINDTREE Job Type : Contract Role: AI Infrastructure Engineer Experience: 15+ Years Relevant Experience : 10+ year Work Location: Pan INDIA Payroll on : People Prime World Wide Notice : Immediate and 15 days Job Description: What You’ll Do Architect the Future: Lead the end-to-end design and development of our AI infrastructure, encompassing hardware, software, networking, and multi-cloud environments Innovate and Evaluate: Assess, select, and implement the best-in-class technologies, tools, and frameworks (e.g., TensorFlow, PyTorch, Kubernetes, Docker) to build and maintain our AI platforms. Optimize for Performance: Engineer and implement infrastructure that scales seamlessly with our evolving AI/ML needs, continuously monitoring and optimizing for both performance and cost-efficiency. Champion Security and Compliance: Define and enforce infrastructure standards and best practices, ensuring unwavering compliance with security policies, data protection regulations, and ethical AI principles. Build Data-Driven Pipelines: Collaborate on the architecture and implementation of highly efficient data pipelines for our AI models, from ingestion and storage to processing and management. Lead and Inspire: Provide technical leadership and mentorship to cross-functional teams, fostering a culture of excellence and best practices in AI infrastructure. Solve Complex Challenges: Diagnose and resolve intricate infrastructure issues, ensuring the high availability and reliability of all our AI systems. Stay Ahead of the Curve: Keep your finger on the pulse of the latest advancements in AI, machine learning, and cloud computing, driving innovation within the organization. Document for Success: Create and maintain comprehensive documentation for all AI infrastructure designs, implementations, and operational procedures. What You’ll Bring Education: A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Experience: 15+ years of experience in infrastructure architecture. A minimum of 3-5 years of dedicated experience in designing and building AI-specific infrastructure. Proven success in deploying scalable and secure AI solutions in cloud environments Extensive, hands-on experience with containerization and orchestration technologies like Docker and Kubernetes. Technical Prowess: Proficiency with the command line and experience with both cloud-native and on-premise data center deployments. A strong understanding of deep learning architectures and the latest developments in Large Language Models (LLMs). Expertise in NVIDIA hardware and software, including performance tuning and diagnostics. Hands-on experience with GPU systems, including performance testing, tuning, and benchmarking. Proficiency in programming languages such as Python. A deep understanding of cloud service models (IaaS, PaaS, SaaS) and cloud-native architectures. In-depth knowledge of networking, storage, and security best practices in a cloud context. Experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation. Familiarity with DevOps and MLOps principles and practices. Soft Skills: Exceptional problem-solving and analytical abilities with a data-driven approach. Excellent communication and interpersonal skills, capable of articulating complex technical concepts to diverse audiences. Proven ability to lead, mentor, and collaborate effectively within a team environment. A strategic mindset with the ability to align technical solutions with overarching business goals. A proactive, adaptable, and continuous learner who thrives in a dynamic technological landscape.