Generative AI Engineer

As a member of the team at this company, you will be deeply involved in building cutting-edge, scalable Generative AI (GenAI) solutions that have a real-world impact. Your expertise in GenAI projects, APIs deployment, debugging endpoints, and proficiency in Python, cloud-native infrastructure, and modern front-end extensions will be instrumental in making a significant contribution. Key Responsibilities: - Design, develop, and deploy scalable Python APIs to serve GenAI models and related functionalities. - Manage containerized applications using Docker and deploy them on Kubernetes clusters to ensure high availability and performance. - Troubleshoot and debug complex issues, including API endpoint failures, latency problems, and deployment inconsistencies. - Develop interactive TypeScript extensions, integrating them seamlessly with backend systems and GenAI services. - Collaborate closely 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 for efficient operations. Qualifications: - 5+ years of experience working on GenAI projects or relevant exposure to generative model-based applications. - Minimum of 2 projects experience in GenAI. - 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 in 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.,