Applied AI Engineer

Role & responsibilities

Job Title: Applied AI Engineer (GenAI & Automation)

Locations: Chennai, India

Role Overview

As a cornerstone of our multi-disciplinary AI Platform & Application Engineering team, you will serve as a primary architect of our organizational transformation. Your mission is the development of next-generation copilots and enterprise automation toolsthe North Star in our current AI strategy. You will oversee the complete lifecycle of these solutions, from initial requirement analysis to final deployment, ensuring our AI initiatives are not merely technical achievements but scalable drivers of business-wide adoption and operational excellence. This role bridges the gap between engineering depth and strategic execution, enabling both internal teams and external collaborators to leverage the full potential of Generative AI.

Key Responsibilities

• Work closely with EHE AI Cohort Coordinators to ensure the new AI ideas are evaluated and move to PoC stage on an accelerated Path.
• Work directly with Solution architect and support in developing and executing the AI strategy for the function in your region.
• Build PoCs, prototypes, and models to validate feasibility and accelerate adoption for end users.
• Develop and lead AI model design and training, ensuring robust performance, accuracy, and adaptability for real-world use cases.
• Deploy and support AI solutions, enabling seamless adoption across internal teams and external stakeholders.
• Provision and manage access to AI platforms, APIs, and model repositories (e.g., Databricks, Snowflakes, AWS, Azure ML).
• Establish compute environments and data pipelines to ensure scalable, high-performance infrastructure for GenAI workloads.
• Foster external collaboration with universities, startups, and industry experts to accelerate innovation.
• Share insights on emerging AI capabilities and trends to influence product roadmaps and organizational strategy.

Enablement Scope

• Licenses & Tools: Manage provisioning of AI platforms, APIs, and development environments to accelerate rapid prototyping and deployment.
  • Infrastructure: Architect and maintain high-performance computing clusters and scalable data pipelines for efficient AI execution.
  • Assessment: Implement structured evaluation frameworks and observability tools to track adoption, performance, and business impact.

Strategic Impact

• Accelerate organizational AI adoption through structured delivery, standardization, and enterprise-grade infrastructure.
• Enable cross-functional innovation by bridging advanced AI capabilities with diverse business needs.
• Drive measurable business value through well-defined KPIs, success metrics, and ROI tracking for automation initiatives.
• Strengthen cross-functional innovation by translating business challenges into well-engineered AI solutions.
• Improve operational efficiency, decision-making, and digital capability maturity through advanced AI systems.

Qualifications

• 3+ years in AI/ML engineering, DevOps, or AI platform development, preferably in automotive or enterprise technology environments.
• Proven experience in model training, large-scale deployment, and cloud infrastructure setup.
• Strong expertise in cloud platforms (Databricks, Snowflakes, AWS, Azure), MLOps practices, and AI frameworks.
• Hands-on experience with LLMs, prompt engineering, RAG architecture, vector databases, LangChain, and LlamaIndex.
• Familiarity with agile delivery and backlog management tools (e.g., JIRA, Confluence).
• Demonstrated ability to lead technical workstreams and mentor teams in fast-paced environments.

Preferred Traits

• High adaptability to emerging AI technologies and evolving automation landscapes.
• Strong analytical mindset with a bias for execution and delivery excellence.
• Comfortable working in high-pressure, cross-functional environments.
• Passion for building scalable AI solutions and driving continuous optimization.

Preferred candidate profile