AI Engineer Full Stack GenAI (Pune)

Only immediate joiner to 30days of notice will be considered Not more than that. AI Engineer Full Stack GenAI Location: Viman Nagar, Pune Experience: 4+ Years Work Mode: Hybrid Working Hours: 11:00 AM 8:00 PM About The Role We are looking for an AI Engineer with strong Full-Stack development experience to build, deploy, and scale production-grade Generative AI applications. The ideal candidate should be hands-on with Next.js, TypeScript, Python, LLM applications, RAG, cloud platforms, and LLMOps. Key Responsibilities - Build and optimize full-stack GenAI applications using Next.js, TypeScript, and Python. - Design, develop, and deploy production-grade AI systems, including Retrieval-Augmented Generation (RAG) solutions for search and discovery. - Develop and integrate LLM-powered applications for content generation, summarization, metadata enrichment, and other AI use cases. - Work with modern GenAI frameworks such as LangChain, LlamaIndex, DSPy, and Hugging Face Transformers. - Implement advanced RAG pipelines, including prompt engineering, chunking strategies, embeddings, and vector database integration. - Deploy and manage LLM applications using cloud-based services such as Azure OpenAI or AWS Bedrock. - Implement LLMOps and observability to monitor latency, cost, accuracy, hallucination, toxicity, and data drift. - Collaborate across the AI and engineering stack to build scalable, reliable, and production-ready solutions. Mandatory Requirements - 4+ years of relevant qualified experience in software, AI engineering. - Strong Full-Stack development experience with hands-on expertise in: - Next.js - TypeScript - Python - Demonstrable experience building and productionizing LLM/GenAI applications. - Strong practical knowledge of RAG architecture, including: - Prompt engineering - Chunking strategies - Embeddings - Vector databases such as Pinecone, Weaviate, or Milvus - Hands-on experience with at least one modern GenAI/LLM framework such as LangChain, LlamaIndex, DSPy, or Hugging Face Transformers. - Experience with managed LLM services such as Azure OpenAI Service or AWS Bedrock. - Strong foundational knowledge of Azure or AWS cloud services. - Experience with containerization and deployment tools such as Docker and CI/CD pipelines (GitHub Actions, Argo, or similar). - Experience deploying and managing production-grade AI/LLM solutions. - Understanding of LLMOps, observability, and monitoring for AI applications. Nice-to-Have Skills - Experience with agentic AI workflows using tools such as AutoGen or CrewAI. - Exposure to multimodal AI models involving text, images, or other data types. - Knowledge of advanced LLM fine-tuning techniques such as LoRA or QLoRA. - Experience with AKS/EKS, serverless functions, and cloud storage. - Strong SQL skills, particularly ClickHouse. - Experience with inference cost optimization and AI application performance tuning. - Experience with monitoring tools such as OpenTelemetry and Prometheus. - Knowledge of model registries and MLOps best practices. Skills: dspy,aws bedrock,llm/genai applications,opentelemetry,crewai,autogen,agentic ai workflows,weaviate,python,typescript,next.js,full stack development,milvus,production-grade ai/llm solutions,deployment tools,azure openai service,ai engineering,llamaindex,prometheus,langchain,pinecone,hugging face transformers .