• Implement AI-driven operations, including log analysis, automated infrastructure updates, and predictive scaling alerts • Benchmark cloud and edge services to improve performance and scalability • Build self-healing infrastructure pipelines that demonstrate advanced AI capabilities • Design, automate, and manage infrastructure using Terraform and AWS services (ECS/Fargate, RDS, S3, IAM) • Build and maintain CI/CD pipelines using GitHub Actions for efficient deployments • Implement and manage observability tools such as Prometheus, Grafana, OpenTelemetry, and Sentry • Handle containerization using Docker and troubleshoot performance issues under load • Collaborate with backend teams to ensure low-latency, scalable, and cost-effective services • Progress into a Staff Platform Engineer or Lead SRE role with end-to-end platform ownership • Contribute to building scalable deployment frameworks for enterprise use cases • Help define best practices for AI-driven DevOps and infrastructure management.

• Design, maintain and tune high performance code. • Apply appropriate approach, best-practice and correct separation of presentation code from business logic. • Implement and support build processes and test environments. • Provide project and task estimates. • Responsible for developing, enhancing, modifying and/or maintaining applications. • Deeply understand requirements and expertly handle Analysis, Design, Coding, Testing and Quality processes.

• Lead the end-to-end design, development, and deployment of enterprise-grade Java applications • Architect and implement scalable, secure, and high-performing solutions preferably on Azure Cloud • Drive the integration of AI/ML capabilities (e.g., APIs, models, automation) into business applications • Collaborate with cross-functional stakeholders to translate business requirements into technical solutions • Provide technical leadership, mentorship, and guidance to a team of developers • Establish and enforce coding standards, best practices, and development frameworks • Oversee code reviews, performance optimization, and system troubleshooting • Manage project timelines, delivery commitments, and resource planning • Ensure CI/CD pipelines, DevOps practices, and cloud-native development standards are followed • Stay updated with emerging technologies, particularly in AI, cloud computing, and microservices architecture

• Design, develop, and maintain scalable and high-performance Java applications • Build and enhance microservices architectures using Spring Boot and related frameworks • Integrate AI/ML and Generative AI capabilities (e.g., OpenAI, Azure AI services, LLM APIs) into applications • Develop intelligent features such as chatbots, recommendation engines, or automation workflows • Deploy and manage applications within Azure Cloud environments • Provide technical guidance, mentorship, and support to junior developers or small teams • Participate in code reviews and enforce best practices in coding, security, and performance • Collaborate with cross-functional teams (Product, QA, DevOps) to deliver end-to-end solutions • Troubleshoot, debug, and optimize applications and AI integrations • Contribute to CI/CD pipelines and DevOps processes • Stay updated on emerging trends in AI, cloud computing, and backend engineering