techstar
Job Description – Senior Engineer – AI/LLM Developer Experience: 4+ Years Role: Senior Engineer – AI/LLM Developer Location: Hyderabad (Preferred)-5 days WFO Prefer Qualification : BE/B.tech, M.tech ,MCA, Masters Overview We are looking for a highly skilled Lead/Senior Engineer – AI/LLM Developer to design, develop, and deploy cutting-edge Generative AI solutions powered by Large Language Models (LLMs). The ideal candidate should have strong experience in AI/ML, transformer models, Retrieval-Augmented Generation (RAG), vector databases, and cloud-based AI deployment. You will play a key role in building scalable, production-ready AI applications while mentoring team members and driving technical excellence. Key Responsibilities Design and develop AI-powered applications using Large Language Models (LLMs). Build, integrate, and deploy LLM-based solutions using OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source models. Develop and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases. Implement advanced prompt engineering techniques to improve AI response quality. Fine-tune transformer-based models for domain-specific use cases. Optimize AI models for latency, scalability, and cost using techniques such as quantization and distillation. Build robust data ingestion and preprocessing pipelines for AI training and inference. Develop AI evaluation frameworks and benchmark model performance. Deploy AI solutions on cloud platforms such as AWS, Azure, or GCP. Containerize AI applications using Docker and orchestrate deployments with Kubernetes. Collaborate with product managers, data scientists, and engineering teams to deliver business solutions. Conduct code reviews, mentor junior engineers, and promote AI engineering best practices. Ensure responsible AI development by following security, privacy, and ethical AI standards. Required Skills & Qualifications 4+ years of software development experience with at least 3 years in AI/ML or Generative AI. Strong proficiency in Python. Hands-on experience with PyTorch, TensorFlow, and Hugging Face Transformers. Experience working with transformer-based models and LLM APIs. Strong understanding of Prompt Engineering and LLM application development. Hands-on experience implementing RAG architectures. Experience with vector databases such as Pinecone, FAISS, ChromaDB, Weaviate, Milvus, or Qdrant. Knowledge of embeddings and semantic search techniques. Experience deploying AI solutions on AWS, Azure, or Google Cloud Platform. Familiarity with Docker and Kubernetes. Strong understanding of REST APIs, microservices, and scalable software architecture. Excellent analytical, debugging, and problem-solving skills. Preferred Skills Experience with LangChain, LangGraph, LlamaIndex, AutoGen, or CrewAI. Knowledge of AI agents and multi-agent architectures. Experience with multimodal AI (text, image, audio, and vision models). Hands-on experience with model optimization techniques including quantization and distillation. Understanding of AI evaluation metrics and benchmarking. Experience with CI/CD pipelines and MLOps. Contributions to open-source AI projects or published AI research are a plus. Knowledge of Responsible AI, AI Governance, and AI Security best practices. Technologies Programming: Python AI/ML Frameworks: PyTorch, TensorFlow, Hugging Face LLM Frameworks: LangChain, LangGraph, LlamaIndex LLMs: GPT, Llama, Claude, Gemini, Mistral Vector Databases: Pinecone, ChromaDB, FAISS, Weaviate, Milvus, Qdrant Cloud Platforms: AWS, Azure, GCP Containers: Docker, Kubernetes Version Control: Git Databases: SQL, NoSQL Deployment: REST APIs, FastAPI, Flask Preferred Candidate Profile Strong expertise in designing enterprise-grade AI applications. Experience delivering production-ready LLM solutions. Ability to work independently and lead technical initiatives. Excellent communication and stakeholder management skills. Preferred Qualification: Master's in AI, B,Tech,MCA,M.Tech Passion for emerging AI technologies and continuous learning.