Sr Python AI Engineer

Key Responsibilities 1. Python Development Design and develop scalable applications and backend services using Python . Develop REST APIs, services, automation scripts, and AI/ML application components. Write clean, maintainable and production-ready Python code. Integrate Python applications with databases, APIs, cloud services, and AI platforms. 2. AI / Generative AI Develop and integrate AI/GenAI capabilities into enterprise applications. Work with Claude and other LLM-based technologies for application development and automation. Use GitHub and AI-assisted development capabilities to improve developer productivity and software delivery. Work with LLM APIs, prompt engineering, tool/API integration and AI-powered workflows. Evaluate AI-generated outputs and ensure appropriate quality, reliability and security. Stay current with emerging GenAI development practices and tools. 3. React / Front-End Development Develop responsive and scalable user interfaces using React.js . Build reusable components and integrate front-end applications with Python-based APIs. Work with JavaScript/TypeScript, HTML and CSS as required. Implement application features based on functional and technical requirements. Troubleshoot and optimize front-end application performance. 4. Databricks & Data Platform Work with Databricks for data processing, analytics and AI-related workloads. Develop and maintain Databricks notebooks, jobs and data pipelines as required. Integrate application and AI workloads with Databricks data platforms. Understand data engineering and data consumption patterns within a lakehouse environment. Collaborate with data engineers and architects on Databricks-based solutions. Required Skills & Experience 6+ years of experience Strong hands-on experience in Python development . Strong hands-on experience with React.js . Practical experience building or integrating AI/Generative AI applications . Experience with Claude / Anthropic or equivalent LLM platforms . Experience with GitHub , including Git-based development workflows; exposure to GitHub Copilot/AI-assisted development is preferred. Hands-on or strong working experience with Databricks . Good understanding of REST APIs and application integration . Good understanding of Docker and containerized applications . Good working knowledge of Kubernetes and application deployment concepts. Understanding of CI/CD pipelines and application release processes . Ability to troubleshoot issues across application, API, data and deployment layers. Strong understanding of software development lifecycle and Agile practices.