Artificial Intelligence Engineer

Position: AI + Backend Engineer

Location: Gurugram

Experience Required: 7–8+ years

We are looking for a highly capable and innovative AI + Backend Engineer to join our dynamic team in Gurugram. The ideal candidate should bring in-depth experience working with Large Language Models (LLMs), Natural Language Processing (NLP), and intelligent agent frameworks, combined with solid backend development skills. This role requires a strong grasp of machine learning operations, API-centric architectures, and distributed systems.

Role & Responsibilities:

• Design and develop advanced AI solutions leveraging LLMs for tasks like content generation, entity extraction, summarization, and intelligent agent development.
• Fine-tune and implement models for dense retrieval, question answering, and semantic search use cases.
• Build and maintain high-performance backend systems and RESTful APIs that support AI model integration.
• Use vector databases and embedding-based retrieval methods to enhance model outputs (e.g., Pinecone, FAISS, Weaviate).
• Apply Retrieval-Augmented Generation (RAG) frameworks to support dynamic and context-aware responses.
• Work closely with ML engineers and researchers to streamline model training, deployment, and optimization processes.
• Monitor and enhance the performance of deployed models and inference pipelines in production environments.
• Set up and manage end-to-end data pipelines for preprocessing, training, and deployment workflows.
• Stay abreast of the latest research and industry developments in the field of LLMs, NLP, and AI agents to continuously improve solutions.

Key Requirements:

• 7–8+ years of experience in AI/ML systems development and backend engineering, with a strong focus on NLP and LLM-based systems.
• Expertise in Python and deep learning libraries such as PyTorch, TensorFlow, and Hugging Face Transformers.
• Strong experience in model fine-tuning, prompt engineering, and building intelligent agent-based applications.
• Practical knowledge of working with vector databases and retrieval mechanisms.
• Proficiency in building and scaling backend platforms using frameworks like FastAPI, Flask, or Django.
• Solid experience with cloud platforms like AWS, Google Cloud Platform, or Azure for AI deployment.
• Skilled in using Docker, Kubernetes, and related tools for model containerization and orchestration.
• Familiarity with MLOps practices, CI/CD pipelines, and model version control.
• Excellent analytical, debugging, and communication skills, with the ability to work effectively in agile, cross-functional teams.