Job Title: AI/LLM Engineer
Experience: 1–5 Years
Location: Mohali
Employment Type: Full-Time
About the Role We are looking for a skilled AI/LLM engineer to join our team and help design, develop, and deploy intelligent applications powered by Large Language Models (LLMs). The ideal candidate has hands-on experience working with generative AI, prompt engineering, and integrating LLMs into real-world products.
Key Responsibilities
- Design, develop, and fine-tune LLM-based applications and features
- Build and optimize prompts for various use cases (chatbots, summarization, content generation, etc.)
- Integrate LLM APIs (OpenAI, Anthropic, Google, open-source models, etc.) into products and workflows
- Work with vector databases (Pinecone, Weaviate, FAISS, ChromaDB, etc.) for retrieval-augmented generation (RAG) systems
- Develop and maintain data pipelines for training, fine-tuning, and evaluation
- Collaborate with product and engineering teams to identify AI-driven solutions to business problems
- Monitor model performance, identify issues, and iterate to improve accuracy, latency, and cost-efficiency
- Stay updated with the latest advancements in AI/ML and LLM technologies
- Write clean, well-documented, and maintainable code
Required Skills & Qualifications
- 1–5 years of experience in AI/ML, NLP, or software development with a focus on LLMs
- Strong proficiency in Python and relevant ML/AI libraries (LangChain, LlamaIndex, Hugging Face, PyTorch, TensorFlow, etc.)
- Practical experience working with LLM APIs (OpenAI, Anthropic, Cohere, etc.)
- Understanding of prompt engineering, fine-tuning, and RAG architectures
- Familiarity with vector databases and embedding models
- Knowledge of REST APIs and backend integration
- Experience with cloud platforms (AWS, GCP, or Azure) is a plus
- Strong problem-solving skills and ability to work in a fast-paced environment
- Good communication skills and ability to collaborate across teams
Nice to Have
- Experience with fine-tuning open-source LLMs (LLaMA, Mistral, etc.)
- Familiarity with MLOps practices and tools
- Exposure to multi-agent systems or AI orchestration frameworks
- Knowledge of Docker/Kubernetes for deployment
Pay: ₹474,793.58 - ₹1,773,385.04 per year
Work Location: In person
