Software Engineer - GenAI Trainee at Larsen & Toubro

Larsen & Toubro is a global powerhouse in engineering, construction, and technology, rapidly expanding its digital and AI capabilities. As a GenAI Trainee, you will be at the forefront of L&T's transformation agenda, building intelligent solutions that power massive infrastructure projects and enterprise services, giving you exposure to real‑world, high‑impact problems rarely seen in typical software roles. The Mumbai office offers a vibrant ecosystem of seasoned engineers and innovators, providing mentorship, fast‑track career pathways, and the chance to contribute to flagship AI initiatives that shape the future of industry. Working at L&T also means access to world‑class resources, from state‑of‑the‑art labs to partnerships with leading AI research institutions. The company’s commitment to continuous learning ensures you’ll receive structured training, certifications, and opportunities to attend global conferences. This blend of cutting‑edge technology, scale, and a culture that rewards curiosity makes the GenAI Software Engineer role a strategic springboard for a lifelong career in AI and advanced engineering.

Prepare by mastering the fundamentals of Generative AI: understand transformer architectures, diffusion models, and prompt engineering. Build a small end‑to‑end project (e.g., text‑to‑image or code generation) and be ready to discuss data pipelines, model selection, training tricks, and deployment challenges. During coding rounds, focus on writing clean, efficient Python/Java code, especially around data preprocessing and algorithmic challenges, as interviewers often gauge your ability to handle large datasets and optimize inference latency. For the system design interview, expect scenarios like designing an AI‑powered content generation service for millions of users. Outline components such as data ingestion, model serving (using containers or serverless), scaling strategies, monitoring, and cost‑optimization on cloud platforms. Demonstrate knowledge of CI/CD for ML, model versioning, and security considerations. Soft‑skill evaluation will center on collaboration—prepare examples where you translated complex AI concepts to non‑technical stakeholders, highlighting L&T’s cross‑functional environment.