AI ENGINEER

Location: Gurgaon, India

Department: Product & Engineering

Experience: 3-9

Role Overview

Key Responsibilities

• Design, build, and deploy scalable AI/ML and Generative AI solutions for real-world applications.
• Lead the complete AI model lifecycle including data collection, preprocessing, training, fine-tuning, evaluation, deployment, and monitoring.
• Develop and optimize LLM-powered applications using modern AI frameworks and architectures.
• Build and maintain robust AI pipelines, APIs, and production-ready AI systems.
• Collaborate cross-functionally with product managers, software engineers, and data teams to integrate AI seamlessly into products and workflows.
• Fine-tune and customize foundation models such as GPT, LLaMA, Mistral, Claude, or similar open-source models.
• Implement Retrieval-Augmented Generation (RAG), vector search, prompt engineering, and agentic AI workflows.
• Ensure high performance, scalability, reliability, and cost optimization of deployed AI systems.
• Stay updated with the latest advancements in AI/ML research and evaluate emerging technologies for practical implementation.
• Mentor junior AI engineers and contribute to technical decision-making and architecture discussions.
• Maintain comprehensive technical documentation and best practices for reproducibility and knowledge sharing.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
• 5–8 years of experience in AI/ML model development and deployment.
• Strong hands-on experience with Generative AI and Large Language Models (LLMs).
• Expertise in Python and AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, or LlamaIndex.
• Strong understanding of NLP, deep learning, multimodal AI, and prompt engineering.
• Experience with vector databases such as Pinecone, Weaviate, ChromaDB, or FAISS.
• Hands-on experience with cloud platforms such as AWS, GCP, or Azure.
• Experience with containerization and deployment tools including Docker and Kubernetes.
• Strong understanding of APIs, scalable backend systems, and AI infrastructure.
• Experience implementing MLOps practices for deployment, monitoring, and model optimization.
• Ability to work in a fast-paced and collaborative environment.

Good to Have

• Experience building AI agents and autonomous workflows.
• Familiarity with fine-tuning techniques such as LoRA, QLoRA, RLHF, or PEFT.
• Knowledge of Computer Vision, Speech AI, or multimodal systems.
• Experience with distributed training and GPU optimization.
• Exposure to AI safety, model evaluation, and governance practices.
• Prior experience leading AI projects or mentoring teams.

What We Offer

• Opportunity to work on cutting-edge Generative AI and LLM-based products.
• Fast-paced, innovative, and collaborative work culture.
• Competitive compensation and accelerated career growth opportunities.
• Access to modern AI infrastructure and tools.
• A chance to shape the future of AI-driven solutions with a forward-thinking team.