Role Overview :

As a Lead AI Engineer based in Hyderabad, you will spearhead the architecture and development of cutting-edge generative AI solutions that redefine how our users interact with complex data. You will operate at the intersection of high-scale backend engineering and advanced machine learning, collaborating closely with product managers, data scientists, and cross-functional engineering teams to translate ambiguous business requirements into robust, production-grade AI systems. Your work will directly influence the scalability and intelligence of our platform, ensuring that our AI-driven features deliver seamless, real-time value to our global customer base.

Key Responsibilities :

- Architect and deploy scalable microservices using Python, FastAPI, and Django to ensure high-performance delivery of AI-powered features for our end-users.

- Design and implement sophisticated RESTful APIs and WebSocket integrations to facilitate low-latency communication between our AI models and client-facing applications.

- Engineer advanced prompt strategies and leverage LangChain frameworks to optimize the output quality and reliability of Generative AI models across various business use cases.

- Manage high-throughput data caching and state management using Redis to enhance the responsiveness and efficiency of our backend infrastructure.

- Mentor junior engineers and conduct rigorous code reviews to maintain high standards of software craftsmanship and system reliability across the development lifecycle.

Required Skillset :

- Demonstrated expertise in building and maintaining production-ready backend systems using Python, with a deep understanding of FastAPI and Django frameworks.

- Proven ability to design resilient microservices architectures and manage complex data flows using Redis, ensuring system stability under high load.

- Advanced proficiency in Generative AI workflows, including practical experience with Prompt Engineering and the LangChain ecosystem to build intelligent, context-aware applications.

- Strong communication skills with the ability to articulate technical trade-offs to non-technical stakeholders and lead collaborative problem-solving sessions within a hybrid work environment.

- A solid foundation in computer science fundamentals, typically supported by a degree in Engineering or a related technical field, combined with 5 to 8 years of hands-on experience in software and AI engineering.