Key Responsibilities
Cloud-Native Application Development
- Build, scale, and maintain cloud-native applications running on Kubernetes
- Develop backend services using Spring Framework and REST-based architectures
- Ensure solutions meet functional, non-functional, scalability, and support requirements
- Align implementations with Global Technology Strategies
AI and Advanced Analytics Integration
- Integrate AI/ML models and APIs for personalization, NLP, recommendations, and decision engines
- Implement Retrieval-Augmented Generation (RAG) and vector database solutions
- Leverage large language models and agentic workflows for real-world use cases
- Apply ethical, secure, and responsible AI development practices
Data Platform Enablement
- Enable data-driven capabilities through integration with Snowflake and enterprise data platforms
- Partner with data engineers to unlock insights for automation and intelligent decisioning
- Support real-time and streaming data use cases where applicable
Collaboration and Technical Leadership
- Partner with architects, product managers, and platform teams to design intelligent features
- Provide mentorship and guidance on AI-related initiatives and best practices
- Contribute across the SDLC from model integration to service deployment
- Share knowledge through internal tech forums, AI guilds, and continuous learning initiatives
Customer-Centric Engineering and Innovation
- Use customer feedback, analytics, and behavioral data to refine AI-driven capabilities
- Promote modernization of legacy platforms into next-generation intelligent systems
- Utilize GenAI tools for prototyping, automated testing, documentation, and code reviews
