Job
Description
About The Role We are on a mission to build cutting-edge, scalable Generative AI (GenAI) solutions that deliver real-world impact. If you've worked on GenAI projects, deployed APIs, debugged endpoints, and enjoy working at the intersection of Python, cloud-native infrastructure, and modern front-end extensionsthis is your opportunity to make a mark. You will join a dynamic and fast-paced team where youll help build, deploy, and maintain GenAI-based systems at scale using tools such as Python, Docker, Kubernetes, and TypeScript-based extensions. Key Responsibilities Design, develop, and deploy scalable Python APIs that serve GenAI models and related functionalities. Manage containerized applications with Docker and deploy them on Kubernetes clusters for high availability and performance. Troubleshoot and debug complex issues, including API endpoint failures, latency problems, and deployment inconsistencies. Develop interactive TypeScript extensions, integrating them with backend systems and GenAI services. Collaborate with data scientists and ML engineers to integrate LLM (Large Language Model) capabilities into production systems. Monitor application health, ensure proper scaling, and implement DevOps best practices. Work cross-functionally with teams across engineering, product, and AI to ensure timely delivery and optimal Qualifications : 5+ years of experience working on GenAI projects or relevant exposure to generative model-based applications. Should have worked min of 2 projects on Gen AI Strong expertise in Python, with a deep understanding of building APIs (using FastAPI, Flask, or similar frameworks). Hands-on experience with Docker for containerization and managing production-grade deployments on Kubernetes. Proven ability to deploy, scale, and monitor APIs in cloud-native environments. Proficiency in TypeScript, with experience building extensions or interactive front-end modules. Familiarity with LLM architectures (e.g., GPT, LLaMA, Claude) and experience working with their APIs or open-source implementations. Strong debugging skills and the ability to investigate and resolve issues across the stack. Nice To Have Experience with API gateways, observability tools (Prometheus, Grafana), or CI/CD pipelines. Familiarity with vector databases or GenAI toolkits like LangChain, RAG frameworks, or OpenAI/Anthropic APIs. Exposure to MLOps practices and model deployment Join Us : Work on frontier AI technology with real-world applications. Join a collaborative and high-performing team passionate about GenAI. Opportunities for growth and ownership in a fast-evolving tech landscape. (ref:hirist.tech) Show more Show less
