Titan Engineering & Automation Limited
Website:
titanteal.com
Job details:
Company Description Titan Engineering & Automation Limited (TEAL), a wholly owned subsidiary of Titan Company Limited, a TATA enterprise, has grown from an in-house engineering team into a global provider of advanced automation and precision manufacturing solutions. TEAL’s Automation Solutions Division delivers turnkey assembly and testing systems for industries such as Automotive, New Energy, Electronics, Medical Devices, and Consumer Packaged Goods, supporting customers from concept to commissioning. The Aerospace & Defence Division specializes in precision components and sub-assemblies for critical systems including aircraft engines, actuations, transmissions, landing systems, environment and underwater systems, and UAVs. The EMS Division offers advanced automation solutions for electronics manufacturing, enabling faster time-to-market, cost efficiency, and zero-defect production for mobile devices, telecom equipment, and other electronic products. Across all divisions, TEAL emphasizes customer-centric, high-value engineering solutions and serves global OEMs and tiered suppliers as a trusted technology partner.
Role Description The Enterprise AI Manager will lead the identification, design, and implementation of AI solutions across TEAL’s automation, manufacturing, and engineering operations. This full-time, on-site role based in Bengaluru involves partnering with business, IT, and engineering teams to develop an AI roadmap, prioritize use cases, and ensure alignment with strategic objectives. Day-to-day responsibilities include overseeing data collection and preparation, guiding model development and deployment, and managing AI platforms and tools for scalability and reliability. The Enterprise AI Manager will establish governance frameworks for AI projects, define best practices, and monitor solution performance to drive continuous improvement. The role also includes mentoring cross-functional teams, collaborating with external vendors or partners when needed, and ensuring responsible, secure use of AI technologies within the organization.
Qualifications
- Candidates should possess strong skills in AI/ML strategy, enterprise architecture, and solution design for automation and manufacturing environments.
- Candidates should possess practical experience with machine learning, deep learning, data analytics, and MLOps practices for deploying and maintaining models in production.
- Candidates should possess proficiency in programming and data tools such as Python, SQL, and common AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Candidates should possess skills in data engineering, including data integration from industrial systems, data quality management, and working with cloud or on-premise data platforms.
- Candidates should possess strong stakeholder management, communication, and project management capabilities to drive cross-functional AI initiatives.
- Candidates should possess knowledge of industrial automation, manufacturing processes, or engineering domains, ideally within automotive, aerospace, electronics, or related sectors.
- Candidates should possess a solid understanding of AI governance, ethics, security, and compliance in an enterprise setting.
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