Role: Lead AI Engineer
Experience: 8+ yrs
Location: MG Road, Bangalore
Work Mode: Hybrid (3 days from office)
About the Role
We are seeking a highly skilled Lead AI Engineer to architect, build and scale AI-powered solutions. The ideal candidate will guide the AI development lifecycleresearch, model building, optimization, deploymentand lead a team of ML/GenAI engineers to deliver high-impact intelligent systems. You will work closely with product, data and engineering teams to define strategy, ensure delivery excellence and drive innovation across AI initiatives.
Key Responsibilities
- Lead design and development of AI/ML and Generative AI solutions end-to-end.
- Build, train, fine-tune and optimize deep learning models (NLP, Vision, LLMs, RAG, multimodal).
- Architect scalable pipelines for data processing, model training and real-time inference.
- Evaluate, fine-tune and integrate LLMs (OpenAI, Llama, Gemini, Claude etc.)
- Implement RAG pipelines, prompt engineering and vector search for enterprise AI apps.
- Deploy models on cloud platforms (AWS/Azure/GCP) using MLOps best practices.
- Manage and mentor AI/ML engineers, perform code and architecture reviews.
- Partner with stakeholders to translate business requirements into technical solutions.
- Research emerging AI trends, POCs and drive innovation programs.
- Ensure responsible AI practicessecurity, bias mitigation, model monitoring.
Required Skills
- Strong expertise in Python, ML frameworks: PyTorch, TensorFlow, Hugging Face.
- Hands-on experience building end-to-end ML/GenAI systems for production.
- Deep understanding of NLP, LLMs, embeddings, transformers, vector DBs.
- Experience with RAG, prompt engineering, agent frameworks (LangChain/LlamaIndex).
- Cloud + MLOps skills: Docker, Kubernetes, CI/CD, model deployment, monitoring.
- Strong grasp of data engineering concepts: ETL, feature store, data pipelines.
- Familiarity with distributed training frameworks (Ray, DeepSpeed, Horovod) is a plus.
- Ability to lead technical discussions, architecture planning & delivery.
Good to Have
- Experience training custom LLMs or multimodal models at scale.
- Knowledge of DataBricks, MLflow, Vertex AI, SageMaker.
- Publications, patents, Kaggle ranks or open-source contributions.
- Domain experience in Healthcare, FinTech, SaaS or Enterprise AI products.
Education
- Bachelor's/Master's degree in Computer Science, AI, Data Science or related field.
Why Join Us
- Work on cutting-edge AI product innovations.
- Ownership, autonomy, and opportunity to build & scale AI teams.
- Competitive compensation with growth opportunities.