This role is for one of the Weekday's clients Salary range: Rs 5500000 - Rs 9000000 (ie INR 55-90 LPA) Experience: 10+ yrs Location: Bengaluru, Karnataka Job Type: Full-Time We are looking for a highly skilled AI Engineer to design, build, and optimize scalable backend systems and intelligent agentic frameworks that power advanced AI applications. In this role, you will work at the intersection of backend engineering, distributed systems, and Generative AI, enabling the deployment of high-performance AI services and intelligent workflows across production environments. As an AI Engineer, you will collaborate with machine learning engineers, platform teams, and infrastructure specialists to build robust AI platforms, integrate large language models into production, and develop scalable inference pipelines. This role is ideal for professionals who are passionate about distributed AI systems, agentic architectures, and building reliable, production-ready AI solutions. ### Key Responsibilities - Design and develop scalable backend systems, microservices, and APIs using Python for AI-driven applications. - Architect distributed infrastructure capable of supporting high-throughput AI workloads and intelligent agent coordination. - Collaborate with machine learning teams to integrate and deploy trained models into production environments. - Build and maintain real-time and batch inference pipelines for AI-powered applications and services. - Develop and optimize AI agent frameworks using modern orchestration technologies and large language models. - Implement and manage Model Context Protocol (MCP) servers to enable seamless communication between AI agents and external tools. - Design and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and knowledge retrieval systems. - Contribute to MLOps and DevOps initiatives by implementing CI/CD pipelines, monitoring, observability, autoscaling, and infrastructure automation. - Optimize system performance, scalability, reliability, and security across AI infrastructure and model-serving environments. - Collaborate with cross-functional engineering teams to continuously improve AI platform architecture and operational efficiency. ### What Makes You a Great Fit - Strong professional experience building production-grade applications using Python. - Expertise in Large Language Models (LLMs) and Generative AI technologies with hands-on experience deploying AI-powered solutions. - Deep understanding of distributed systems, system design, asynchronous programming, and network architecture. - Experience building AI agents using frameworks such as LangChain or similar agent orchestration platforms. - Strong knowledge of Model Context Protocol (MCP) and building interoperable AI agent ecosystems. - Hands-on experience with vector databases such as FAISS, Pinecone, or Weaviate for knowledge retrieval and RAG implementations. - Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or JAX and model-serving platforms including Triton Inference Server, TorchServe, ONNX Runtime, or Ray Serve. - Proficiency with Docker, Kubernetes, cloud platforms (AWS, Azure, or GCP), Infrastructure as Code, and modern CI/CD practices. - Experience working with SQL/NoSQL databases, Redis, Kafka, RabbitMQ, and scalable backend architectures. - Strong analytical, problem-solving, and collaboration skills with a passion for building secure, scalable, and production-ready AI systems. - Exposure to multi-agent systems, AI safety, advanced LLM architectures, or open-source AI projects is an added advantage.