I am a Technical Manager with over 13 years of experience leading the design, development, and modernization of large-scale, cloud-native platforms across banking, financial services, retail, transportation, and media domains. My career spans hands-on engineering, architecture, and technical leadership, allowing me to effectively bridge business goals with robust, scalable, and future-ready technology solutions.As a Technical Manager, my primary focus is enabling teams to deliver high-quality systems while ensuring architectural consistency, operational excellence, and long-term scalability. I bring a strong engineering foundation in Java and the Spring ecosystem, combined with practical experience in Node.js, TypeScript, Go, and Python. This background allows me to guide teams with informed technical decisions, review complex designs, mentor engineers, and remain close to the code when needed—particularly in critical systems involving data, performance, and reliability.I have led multiple teams building cloud-native microservices using Spring Boot, Spring WebFlux, Spring Data, Spring Security, and Spring Cloud, deployed across containerized and serverless environments. These systems support high-volume, low-latency workloads such as financial transactions, inventory management, and real-time analytics. I emphasize clean architecture, SOLID principles, and domain-driven design to ensure systems remain maintainable as teams and requirements scale.A key area of my leadership experience lies in **data platforms and AI-ready architectures**. I have overseen the development of event-driven systems using Apache Kafka and Apache Flink that process massive streams of transactional, telemetry, and trading data. These platforms form the backbone for analytics and machine learning initiatives, enabling downstream use cases such as anomaly detection, forecasting, trend analysis, and risk assessment. I work closely with data engineers, ML engineers, and analytics teams to ensure data pipelines are reliable, well-governed, and suitable for AI/ML consumption.I actively guide teams in designing systems that support AI and machine learning workloads, even when the core application is not an ML product itself. This includes ensuring data quality, schema evolution, observability, and scalable ingestion patterns. I have promoted architectural patterns that allow AI models to be integrated as first-class components—whether through real-time inference APIs, batch scoring pipelines, or feature-serving layers—without compromising system stability.My experience with GraphQL has been particularly valuable in AI-enabled and analytics-heavy systems. I have led initiatives to introduce GraphQL alongside REST APIs, enabling flexible data access patterns that reduce over-fetching and improve performance for dashboards, reporting tools, and intelligent applications. From a management perspective, I focus on governance, schema design standards, and team adoption strategies to ensure GraphQL remains a productivity enabler rather than a complexity burden.From a people and delivery standpoint, I have led cross-functional teams through modernization efforts, cloud migrations, and platform transformations. I am deeply involved in sprint planning, technical roadmap definition, code reviews, production readiness, and incident analysis. I strongly advocate for automation, CI/CD best practices, and strong test coverage, recognizing that AI-enabled systems are only as trustworthy as the platforms that support them.I also emphasize **AI-informed operations (AIOps)** and observability. By leveraging metrics, logs, and traces through tools such as New Relic, Splunk, and CloudWatch, I help teams detect anomalies early, reduce mean time to recovery, and continuously improve system reliability. These practices naturally align with AI-driven monitoring and predictive insights, which I see as a growing area of impact for technical leadership.Throughout my career, I have delivered solutions for globally recognized organizations including Cognizant, Walmart, UBS, Warner Bros. Discovery, Penske Truck Leasing, and State Street. Working in highly regulated and large-scale environments has strengthened my ability to balance innovation with compliance, security, and risk management—critical skills for a Technical Manager operating at enterprise scale.Today, I define my role as a Technical Manager who builds strong engineering cultures, scalable platforms, and AI-ready systems. I am passionate about mentoring engineers, modernizing legacy platforms, and enabling organizations to move confidently toward data-driven and AI-powered solutions while maintaining the reliability and performance that enterprise systems demand.