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 professional 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: llm/genai applications,autogen,next.js,production-grade ai/llm solutions,dspy,python,agentic ai workflows,hugging face transformers,llamaindex,deployment tools,ai engineering,weaviate,pinecone,opentelemetry,langchain,crewai,azure openai service,typescript,milvus,aws bedrock,prometheus,full stack development
