Tata Electronics Private Limited (TEPL) is a greenfield venture of the Tata Group with expertise in manufacturing precision components. Tata Electronics (a wholly owned subsidiary of Tata Sons Pvt. Ltd.) is building India’s first AI-enabled state-of-the-art Semiconductor Foundry. This facility will produce chips for applications such as power management IC, display drivers, microcontrollers (MCU), and high-performance computing logic, addressing the growing demand in markets such as automotive, computing and data storage, wireless communications, and artificial intelligence.
The Tata Group operates in more than 100 countries across six continents, with the mission: 'To improve the quality of life of the communities we serve globally, through long-term stakeholder value creation based on leadership with Trust.'
Key Responsibility
Own the product vision and roadmap for GenAI-powered solutions in manufacturing, driving alignment between business goals and technical delivery
Collaborate with cross-functional teams (engineering, data science, business stakeholders) to define, prioritize, and deliver AI/GenAI features that create measurable impact on manufacturing operations.
Translate manufacturing use cases into robust GenAI product requirements, ensuring solutions are scalable, secure, and compliant with enterprise standards.
Oversee the end-to-end lifecycle of GenAI product delivery—from ideation and prototyping to production deployment, monitoring, and adoption tracking.
Champion the integration of GenAI workflows across manufacturing, supply chain, finance, and shop floor processes for operational excellence.
Partner with technical leaders to implement CI/CD pipelines, infrastructure-as-code, and containerized deployments for GenAI applications.
Ensure responsible AI adoption by embedding observability, security, and governance frameworks in all GenAI products.
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Proven experience as a product owner or manager in GenAI, LLM architectures, and multi-agent orchestration within manufacturing or enterprise environments.
Strong understanding of DevOps, cloud-native and on-prem engineering, and modern AI deployment practices (CI/CD, GitOps, Kubernetes, monitoring).
Demonstrated ability to balance technical depth with business impact, driving agile execution in fast-paced, ambiguous settings
Passion for digital transformation and shaping Industry 4.0 through GenAI innovation
Experience
8–10 years’ experience in product ownership or technical leadership, with at least 3–5 years focused on GenAI and enterprise AI initiatives.
Hands-on expertise with GenAI frameworks (LangChain, LlamaIndex, RAG architectures) and LLM deployment strategies.
Proficiency with cloud platforms (Nvidia, AWS, Azure, GCP), serverless computing, and container orchestration (EKS, AKS, GKE).
Strong understanding of data pipelines, lakehouse/lake architectures, and vector databases (e.g., Pinecone, Milvus, OpenSearch).
Experience in manufacturing, semiconductors, or electronics domains is highly desirable.
Prior experience in manufacturing, semiconductors, or electronics domains is a strong plus.
Certifications in PMP, Agile, SAFe, or Cloud DevOps (AWS/Azure/GCP) are desirable.
Competencies
Teamwork
Agility
Customer Empathy
Purposeful Pursuit of Goals
Pioneering
Deep Domain Knowledge
Future Ready
Purpose
Tata Electronics Private Limited (TEPL) is a greenfield venture of the Tata Group with expertise in manufacturing precision components. Tata Electronics (a wholly owned subsidiary of Tata Sons Pvt. Ltd.) is building India’s first AI-enabled state-of-the-art Semiconductor Foundry. This facility will produce chips for applications such as power management IC, display drivers, microcontrollers (MCU), and high-performance computing logic, addressing the growing demand in markets such as automotive, computing and data storage, wireless communications, and artificial intelligence.
The Tata Group operates in more than 100 countries across six continents, with the mission: 'To improve the quality of life of the communities we serve globally, through long-term stakeholder value creation based on leadership with Trust.'
Key Responsibility
Own the product vision and roadmap for GenAI-powered solutions in manufacturing, driving alignment between business goals and technical delivery
Collaborate with cross-functional teams (engineering, data science, business stakeholders) to define, prioritize, and deliver AI/GenAI features that create measurable impact on manufacturing operations.
Translate manufacturing use cases into robust GenAI product requirements, ensuring solutions are scalable, secure, and compliant with enterprise standards.
Oversee the end-to-end lifecycle of GenAI product delivery—from ideation and prototyping to production deployment, monitoring, and adoption tracking.
Champion the integration of GenAI workflows across manufacturing, supply chain, finance, and shop floor processes for operational excellence.
Partner with technical leaders to implement CI/CD pipelines, infrastructure-as-code, and containerized deployments for GenAI applications.
Ensure responsible AI adoption by embedding observability, security, and governance frameworks in all GenAI products.
Essential Attributes
Proven experience as a product owner or manager in GenAI, LLM architectures, and multi-agent orchestration within manufacturing or enterprise environments.
Strong understanding of DevOps, cloud-native and on-prem engineering, and modern AI deployment practices (CI/CD, GitOps, Kubernetes, monitoring).
Demonstrated ability to balance technical depth with business impact, driving agile execution in fast-paced, ambiguous settings
Passion for digital transformation and shaping Industry 4.0 through GenAI innovation
Experience
8–10 years’ experience in product ownership or technical leadership, with at least 3–5 years focused on GenAI and enterprise AI initiatives.
Hands-on expertise with GenAI frameworks (LangChain, LlamaIndex, RAG architectures) and LLM deployment strategies.
Proficiency with cloud platforms (Nvidia, AWS, Azure, GCP), serverless computing, and container orchestration (EKS, AKS, GKE).
Strong understanding of data pipelines, lakehouse/lake architectures, and vector databases (e.g., Pinecone, Milvus, OpenSearch).
Experience in manufacturing, semiconductors, or electronics domains is highly desirable.
Prior experience in manufacturing, semiconductors, or electronics domains is a strong plus.
Certifications in PMP, Agile, SAFe, or Cloud DevOps (AWS/Azure/GCP) are desirable.
