Role Overview :

As an AI Engineer specializing in MLOps and LLMs, you will be at the forefront of designing, deploying, and scaling sophisticated generative AI solutions. You will work closely with cross-functional data science and engineering teams to bridge the gap between experimental model development and production-grade software. Your daily contributions will involve building robust pipelines that ensure the reliability, scalability, and performance of LLM-based applications, directly impacting how our clients leverage AI to solve complex business challenges at scale.

Key Responsibilities :

- Architect and maintain end-to-end CI/CD pipelines to automate the deployment and monitoring of machine learning models in production environments.

- Design and implement scalable LLM orchestration workflows using frameworks like Langchain, Langgraph, and Llamaindex to enhance application intelligence.

- Manage containerized environments using Docker and Kubernetes to ensure high availability and efficient resource utilization for AI workloads.

- Optimize model performance and latency by implementing advanced MLOps practices, ensuring seamless integration with existing cloud infrastructure.

- Collaborate with stakeholders to translate business requirements into technical AI roadmaps, ensuring that deployments meet stringent security and performance standards.

- Mentor junior engineers on best practices for code quality, system architecture, and the lifecycle management of large-scale AI systems.

Required Skillset :

- Demonstrated expertise in Python programming with a focus on building production-ready AI applications and backend services.

- Proven ability to design and manage complex CI/CD pipelines, ensuring rapid and reliable delivery of machine learning models.

- Strong hands-on experience with containerization and orchestration tools, specifically Docker and Kubernetes, in a cloud-native environment.

- Deep technical proficiency in working with Large Language Models, including the application of Langchain, Langgraph, and Llamaindex for real-world use cases.

- Exceptional problem-solving skills with the ability to communicate technical complexities to non-technical stakeholders effectively.

- A minimum of 7 to 12 years of professional experience in software engineering or machine learning operations.

- Ability to thrive in a collaborative, high-performance environment across Bangalore, Pune, or Delhi/NCR locations.