Role description 1 The Context Purpose of the Job TSL is seeking an AI Engineer to lead our advancement toward Industry 5 0 by developing and implementing a comprehensive AI strategy focused on creating creative operating models that seamlessly integrate human and machine intelligence This key role is centered on writing code analyzing data and building robust ML and AI pipelines to drive significant improvements in business performance The candidate should be proficient in Python data science ML Time series optimisation classification regression problems and deep learning modules CNN RNN LSTM as well as cutting-edge Generative AI concepts like Agentic Design RAG prompt-to-template strategies and chunking strategies This position requires expertise in decentralized architectures proficiency with SQL NoSQL and PostgreSQL databases and the ability to deploy solutions across multi-cloud platforms GCP AWS Azure leveraging serverless technologies like Cloud Run Cloud Functions and Lambda alongside Kubernetes for container orchestration Key Objective Overall Job Responsibility Main Purpose Strategic AI Vision Leadership Develop and champion a clear AI vision by conceptualizing autonomous business models that leverage Generative AI including Agentic Design and RAG architectures to redefine the TSL value chain Collaborate with stakeholders to define solution objectives deliverables and timelines Hands-On AI Implementation Deployment Lead the end-to-end design development and deployment of AI solutions using Python and its data science ecosystem Architect and build robust ML AI pipelines and deploy them on multi-cloud serverless platforms GCP Cloud Run AWS Lambda Azure Functions and Kubernetes GKE Advanced Model Development Innovation Direct the AI learning trajectory by applying Deep Learning models CNN RNN LSTM and advanced Generative AI techniques including innovative chunking strategies and prompt-to-template frameworks to solve complex business challenges Technical Leadership Data Architecture Provide technical guidance to internal and external partners to build scalable AI solutions on decentralized architectures Ensure seamless implementation and data integrity through proficient use of SQL PostgreSQL and NoSQL databases Program Change Management Spearhead the end-to-end transformation process from model conception to production deployment while managing change to ensure successful business adoption Effectively multitask across multiple AI projects prioritizing technical resources to meet competing deadlines Communication Stakeholder Engagement Effectively translate and communicate complex model performance metrics data-driven insights and strategic project direction to diverse audiences including senior management business users and external partners to ensure alignment and buy-in Relevant Experience Experience of working in high performance teams delivering AI solutions Experience of working in cross-functional collaborative environment Good understanding of mining manufacturing supply chain commercial processes along with knowledge of technology applications in these domains would be preferred Skills Technical Competencies Deep understanding of AI ML algorithms and techniques including Generative AI models e g large language models SLM diffusion models supervised unsupervised and reinforcement learning Expertise in AI architecture design and implementation Familiarity with cloud platforms AWS Azure GCP big data technologies Hadoop Spark and AI ML frameworks TensorFlow PyTorch Understanding of frameworks methods like RAG Fine-tuning Pre-training Agentic AI Proficiency in Prompt Engineering utilizing tools accessing APIs and collaborating with AI agents In-depth understanding of the LangChain Google ADK etc framework for building and optimizing Large Language Model LLM applications Experience with data engineering and data management including data cleaning preprocessing feature engineering and data pipelines Proficiency in programming languages Python R or similar languages are essential Knowledge of model deployment and monitoring Experience with MLOps practices and tools for deploying and managing AI models in production environments Understanding of bias mitigation privacy preservation and responsible AI practices Familiarity with various AI applications and their business implications across different functional areas Ability to design scalable robust and maintainable AI systems Understanding of IT-OT architecture Behavioural Competencies Proficiency in forging strong Customer Supplier Partner relationships Managing multiple AI projects simultaneously ensuring timely and successful delivery within budget Target timeline oriented Effectively communicating technical concepts to both technical and non-technical stakeholders managing expectations and building consensus Understanding the business context and translating business needs into technical solutions Other details Educational qualifications BE BTech ME MTech MSc Maths Stats MBA PGDM equivalent from distinguished Institutions