Artificial Intelligence Engineer

Bupa; Gurugram District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Bupa is seeking a Lead AI Engineer with hands-on expertise to design, develop and deploy AI/ML systems at scale, with a deep focus on AI, ML, DL, Generative AI, NLP and LLM technologies.

This is a hands-on technical leadership role where you will lead model development, experimentation, optimization and productionization, collaborating with data and product teams to deliver scalable AI solutions.

Qualifications

• Bachelor's or higher in CS/AI/ML or related field.
• Experience with ML/DL model development and deployment.

Responsibilities

• Lead design and development of scalable AI/ML solutions.

Skills

Python

PyTorch

TensorFlow

NLP

LLM

MLOps

Docker

Cloud

Education

Bachelor's in CS/AI/ML

Master's preferred

Tools

LangChain

Vector Databases

LlamaIndex

Job description

We are looking for a highly experienced Lead AI Engineer who is a core AI/ML professional with strong hands‑on expertise in designing, developing, and deploying AI/ML systems at scale.

The ideal candidate should have a deep understanding of Artificial Intelligence, Machine Learning, Deep Learning, Generative AI, NLP and LLM technologies, along with strong Python programming and production engineering capabilities.

This is a hands‑on technical leadership role. We are looking for someone who can work beyond simply integrating third‑party AI APIs and can contribute to AI model development, experimentation, optimization, evaluation and productionization.

Key Responsibilities

• Lead the design and development of scalable AI/ML solutions for complex business problems.
• Develop, train, fine‑tune, evaluate and optimize machine learning and deep learning models.
• Work extensively with Generative AI, LLMs, NLP and advanced AI architectures.
• Design AI pipelines covering data preparation, model training, evaluation, deployment and monitoring.
• Build and productionize AI models using Python and modern AI/ML frameworks.
• Work on LLM fine‑tuning, prompt engineering, RAG, embeddings and vector databases where applicable.
• Evaluate AI models using appropriate accuracy, performance and business metrics.
• Research and implement state‑of‑the‑art AI/ML techniques.
• Collaborate with Data Engineering, Backend Engineering, Product and Business teams.
• Establish best practices around model versioning, experimentation, reproducibility and AI governance.
• Mentor senior engineers and guide the technical direction of AI initiatives.
• Drive AI solutions from POC → production → continuous optimization.

Mandatory Technical Skills

Core AI / Machine Learning

• Strong hands‑on experience in Machine Learning and Deep Learning
• Strong understanding of Supervised & Unsupervised Learning
• Experience with model development, training, validation and optimization
• Strong knowledge of NLP and/or Computer Vision
• Experience with neural network architectures and modern deep learning techniques

Generative AI / LLM

• Strong practical experience with Generative AI and Large Language Models
• Experience with LLM fine‑tuning / customization
• RAG (Retrieval‑Augmented Generation)
• Prompt Engineering
• Embeddings and Vector Search
• AI/LLM evaluation
• Experience with frameworks such as LangChain, LlamaIndex or equivalent

Programming & Frameworks

• Strong proficiency in Python
• Experience with PyTorch and/or TensorFlow
• Strong understanding of NumPy, Pandas and ML ecosystem
• Experience developing production‑grade AI applications and services

AI Infrastructure / Deployment

• Experience deploying AI/ML models into production
• Knowledge of MLOps / ML lifecycle management
• Experience with Docker and containerized deployments
• Knowledge of cloud platforms such as AWS, GCP or Azure
• Understanding of model monitoring, performance optimization and scalability

Good to Have

• Experience with Generative AI Agents / Agentic AI
• Experience with multimodal AI
• Knowledge of Transformer architectures
• Experience with open‑source LLMs such as Llama, Mistral or similar
• Experience with distributed model training/inference
• Knowledge of Kubernetes
• Experience with MLflow, Kubeflow or similar MLOps platforms
• Strong understanding of AI system architecture and scalability
• Proven ability to technically lead AI engineering teams/projects
• Strong problem‑solving and architectural thinking
• Ability to independently drive AI initiatives from concept to production
• Ability to mentor and review the work of AI/ML engineers
• Strong communication and stakeholder‑management skills
• Comfortable working in a fast‑paced, product‑focused environment

Ideal Candidate

We are specifically looking for a Core AI Engineer, not someone whose experience is limited to calling OpenAI/LLM APIs or building basic chatbot applications.

The ideal candidate should have a strong foundation in AI/ML algorithms, deep learning, model development, experimentation and production AI systems, combined with modern GenAI/LLM expertise.

Education

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering or a related field.
• Advanced degree in AI/ML or related specialization will be an advantage.

Key Skills

Core AI | Machine Learning | Deep Learning | Generative AI | LLM | NLP | Python | PyTorch | TensorFlow | RAG | LLM Fine‑Tuning | Transformers | LangChain | Vector Databases | MLOps | AI Model Deployment | Cloud | AI Architecture