AI Platform Architect

TVS Motor Company; Bengaluru; On-site; INR 4,500,000 - 7,000,000; Full time

Job summary

TVS Motor Company is seeking a seasoned AI Architect to design and launch an enterprise‑grade AI platform across sales, service, manufacturing and supply chain. The role drives scalable AI adoption and supports no‑code, low‑code and high‑code developer personas.

You will mentor engineers, establish governance, and ensure secure, reliable production delivery of AI initiatives with a broad cross‑functional impact.

Qualifications

• Master’s degree in Computer Science, AI, Data Science or related field.
• 15+ years in statistics, ML, AI/ML design, and enterprise software delivery.
• Experience mentoring engineers and influencing senior stakeholders in automotive or manufacturing.

Responsibilities

• Define enterprise AI architecture blueprint for scalable platforms.
• Translate business priorities into production‑ready AI solutions.
• Establish MLOps standards, governance and data privacy practices.
• Mentor senior AI engineers on architecture and delivery.
• Provide hands‑on reviews and production‑readiness support for critical AI initiatives.

Skills

AI architecture

MLOps

Python

Cloud architectures

Enterprise architecture

Leadership

Mentoring

Stakeholder management

Education

Master's degree in CS/AI/DS

Tools

SQL

Spark

APIs

CI/CD

Containers

Job description

TVS Motor Company is a reputed two and three-wheeler manufacturer globally, championing progress through Sustainable Mobility with four state-of-the‑art manufacturing facilities in Hosur, Mysuru and Nalagarh in India and Karawang in Indonesia. Rooted in our 100-year legacy of Trust, Value, and Passion for Customers and Exactness, we take pride in making internationally aspirational products of the highest quality through innovative and sustainable processes. We are the only two‑wheeler company to have received the prestigious Deming Prize. Our products lead in their respective categories in the J.D. Power IQS and APEAL surveys. We have been ranked No. 1 Company in /the J.D. Power Customer Service Satisfaction Survey for consecutive four years. Our group company Norton Motorcycles, based in the United Kingdom, is one of the most emotive motorcycle brands in the world. Our subsidiaries in the personal e‑mobility space, Swiss E‑Mobility Group (SEMG) and EGO Movement have a leading position in the e‑bike market in Switzerland. TVS Motor Company endeavours to deliver the most superior customer experience across 80 countries in which we operate.

Purpose of the Role

Designand launch enterprise‑gradeAI platform and solutionarchitecturefor TVS Motor across sales, marketing, service, manufacturing, supply chain, new product development and corporate functions. Enable scalable AI adoption that improves customer, partner (dealer, supplier etc) and employee experiences and supports no‑code, low‑code and high‑code developer personas.

Key Responsibilities

• AI Architecture Strategy: Define TVS Motor’s enterprise AI architecture blueprint to enable secure, scalable and reusable AI platforms across business clusters.
• Solution Design and Review: Translate business priorities into production‑ready AI solution designs and review solution architecture with product, data, engineering, security and business teams.
• AI Governance: Establish standards for MLOps, model hosting, observability, responsible AI, data privacy and lifecycle governance.
• Engineering Mentorship: Mentor senior AI engineers on architecture patterns, engineering excellence and production‑grade delivery.
• Hands‑on Delivery Support: Provide hands‑on architecture reviews, technical problem‑solving and production readiness support for critical AI initiatives.

Key Performance Indicators (KPIs)

• Architecture Reuse and Cost Efficiency: Adoption of approved architecture patterns and reusable platform services to reduce duplication and delivery cost.
• Speed to Production: Reduction in cycle time from use‑case approval to production deployment through standard designs and reusable components.
• Quality and Reliability: AI solutions meeting agreed standards for reliability, security, observability, responsible AI, privacy and production readiness.
• Engineering Enablement: Improvement in senior AI engineer capability through mentoring, architecture reviews and technical problem‑solving support.
• Automotive Process Understanding: Apply AI architecture to sales, service, manufacturing, supply chain, product development and corporate functions.
• Cross‑functional Solution Leadership:Influence and align business, product, data, engineering, security and operations teams to scale AI solutions from concept to adoption.
• Hands‑on Coding and Engineering:Proficiency in Python and modern engineering practices for AI prototyping, code reviews and production support.
• AI PlatformArchitecture: Design AI/ML platforms, model services, feature pipelines, APIs, MCPs and reusable components for enterprise use, with strong working knowledge of SQL, Spark and structured/unstructured data such as tables, text, voice and video.
• MLOps and Model Lifecycle:Expertise in ML CI/CD, deployment, monitoring, evaluation, versioning, observability and reliability.

GenAI and Agentic AI: Working knowledge of statistics, ML algorithms, LLMs, RAG, prompt engineering, LLM fine‑tuning, agent workflows, evaluation, guardrails and responsible AI.

• Cloud and Integration Architecture: Experience with cloud‑native AI services, containers, APIs, event‑driven integration, security patterns and enterprise systems.
• Strategic Communication and Influence: Explains complex AI choices clearly, builds alignment and influences senior stakeholders.
• Cross‑functional Collaboration: Builds effective relationships across business, product, data, engineering, security and operations teams.
• Structured Problem Solving: Applies analytical thinking, business acumen and sound judgment to resolve architecture and delivery trade‑offs.
• Execution Discipline: Drives outcomes with ownership, customer focus, planning discipline and continuous improvement.

Experience and Education

• Education:Master’s degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Machine Learning, Electronics, Information Technology or related engineering disciplines.
• Experience: 15+ years across statistics, machine learning, AI/ML solution design, enterprise architecture, software engineering and production‑scale AI delivery (Preferably product companies).
• Leadership Exposure: Experience mentoring senior engineers, influencing business stakeholders and delivering AI solutions in enterprise, automotive or manufacturing environments.