Experience : 7- 8+ years

Job Description :

We are seeking a highly skilled and experienced AI + Backend Engineer to join our team in Gurugram. The ideal candidate will have deep expertise in Large Language Models (LLMs), Natural Language Processing (NLP), and AI agents, along with strong backend development skills.

This role requires a solid understanding of machine learning workflows, distributed systems, and API-driven and Event-driven architectures. The candidate must possess strong problem-solving abilities, excellent coding skills, and a proactive approach to innovation.

Key Responsibilities :

- Design, develop, and optimize LLM-based AI systems for text generation, information retrieval, and agent-based applications.

- Expertise towards fine tuning and using search and dense information retrieval model

- Implement and fine-tune LLM models for tasks such as entity recognition, summarization, and question-answering.

- Architect and develop backend services and APIs that integrate AI models with scalable infrastructure.

- Leverage vector databases, embeddings, and retrieval-augmented generation (RAG) to enhance AI-driven solutions.

- Collaborate with ML researchers and engineers to improve model efficiency and deployment strategies.

- Monitor, troubleshoot, and optimize model and agent inference performance in real-world applications.

- Ensure robust data pipelines for preprocessing, model training, and inference workflows.

- Stay updated with the latest advancements in LLMs, NLP, and agent-based architectures to drive innovation.

Required Skills & Qualifications :

- 7- 8+ years of experience in AI/ML and backend development, with a strong focus on NLP and LLMs.

- Proficiency in Python, with experience in libraries such as PyTorch, TensorFlow, Hugging Face Transformers, and agentic frameworks.

- Expertise in LLM fine-tuning, prompt engineering, and agent-based frameworks.

- Experience with vector databases (e.g., Pinecone, FAISS, Weaviate) and embeddings-based retrieval.

- Strong backend development skills using FastAPI, Flask, or Django.

- Experience in designing and deploying scalable AI architectures in cloud environments (AWS, GCP, or Azure).

- Knowledge of containerization (Docker, Kubernetes) and model deployment techniques.

- Familiarity with CI/CD pipelines, model versioning, and MLOps best practices.

- Excellent problem-solving skills, logical thinking, and the ability to work in an agile environment.

- Strong communication and collaboration skills to work across AI, engineering, and product teams