Bengaluru, Karnataka, India
👨💻 Software Engineer | Backend, Cloud, Microservices, Distributed Systems | Python, AWS, Terraform, CloudFormation I’m a versatile Software Engineer with 2+ years of experience designing and delivering high-performance, scalable, and maintainable systems. I specialize in building cloud-native backend services, microservices architectures, and distributed platforms with a strong focus on reliability, efficiency, and operational excellence. 🚀 Experienced in Python, AWS (Lambda, EC2, S3, DynamoDB, SQS, SNS, API Gateway, CloudWatch), Infrastructure as Code using Terraform and CloudFormation, and event-driven architectures. I build production-ready systems capable of scaling to meet high-demand workloads. ☁️ Comfortable across technologies and domains, I tackle complex backend, cloud, and infrastructure challenges, emphasizing clean code, maintainable architectures, and automation. 🤝 I actively mentor, lead knowledge-sharing sessions, and foster high-performing engineering cultures, driving team efficiency and best practices. 🔍 Always seeking impactful opportunities in backend and cloud engineering, where I can architect scalable systems, solve complex technical problems, and deliver business-critical solutions.
• Working under Digital X: the technology and innovation division driving digital transformation, AI, and data-driven banking solutions. • Business Unit: Retail Banking (Digital X) • Contributing to Retail Banking → delivering customer-first solutions for 20M+ retail customers • Implementing cloud-native, scalable systems → improving performance, reliability, and maintainability • Partnering with cross-functional teams → accelerating fintech innovation in a regulated environment
• Redesigned playlist recording workflow by implementing a persistent socket connection between a Python-based PEX Driver (`stream-record-job-runner`) and the playout service using Protocol Buffers. Enabled real-time playlist updates, reducing job update latency from ~8s to <1s and cutting redundant event processing by 95%. • Developed a Cease Recorder API to terminate stale or disconnected EC2 instances in both TEST and PROD environments. Empowered non-admin users to manage lifecycle events, reducing cloud costs by 35% and improving instance management efficiency by 40%. • Led end-to-end design and development of a system to upload recorded MXF files to customer-specific S3 buckets post live-streaming, and register assets via AWS EventBridge. Improved job status propagation time by 35% and increased system throughput by 20%. • Developed chunked recording mechanism for live streams, where each segment was uploaded to S3 and later stitched into a full MXF asset using ORT (Playout Engine) Site APIs via JSON RPC. Enhanced stream handling efficiency by 35% and reduced file upload latency by 20%. • Engineered and maintained multiple backend microservices, contributing to their design, development, observability, and CI/CD pipelines within a cloud-native ecosystem (AWS Lambda, EC2, S3, DynamoDB, EventBridge, SNS, SQS). • Actively mentor interns, driving onboarding, task planning, technical upskilling, and performance feedback via structured 1:1 sessions and KT sessions.
• Developed backward-compatible CRUD APIs in the playlist-management service to store playlist-import configurations in DynamoDB, replacing S3 bucket tags. Authored a tenant-wise migration script that transitioned data for 100+ tenants, reducing config retrieval time by 30% and ensuring a seamless switchover. • Built a CI/CD pipeline for the stream-record-job-runner Python PEX Driver using GitHub Actions. Automated changelog generation, semantic versioning, and publishing to AWS CodeArtifact. Removed large PEX binaries (initially ~40 MB and growing), reducing repository bloat by 50% and cutting EC2 startup time by 30% through dynamic artifact retrieval. • Conducted a successful POC to upload MXF files from ORTMC (OvertureRealTime-MediaConnect) to S3 and register them in the Content Service. This work led to the creation of the `stream-record-job-runner` PEX Driver, enabling automated EC2 instance management and recording control via ORT (Playout Engine) APIs, streamlining operations by 35%. • Improved observability across core microservices by integrating OpenTelemetry semantic conventions, increasing trace uniformity and reducing debugging time by 20%. • Optimized AWS Lambda usage in the data-translation service by implementing an SNS filter policy, triggering translations only for specific file extensions. Reduced unnecessary invocations by 50% and improved processing efficiency by 30%. • Strengthened service quality and reliability by writing unit tests, fixing 30+ bugs across multiple microservices, and contributing to code refactors leading to a 20% improvement in code quality. • Enhanced team productivity by documenting workflows and architecture in Confluence, reducing onboarding time for new developers by 15%. • Established a Copybara-based workflow to manage API specifications and autogenerated clients in a shared monorepo, improving code consistency and simplifying client integration across services by 30%.
• Gained hands-on experience with AWS Lambda, API Gateway, DynamoDB, and boto3 by developing and deploying serverless functions. • Designed and maintained YAML-based AWS CloudFormation templates, along with Swagger/OpenAPI specifications for service documentation and deployment consistency. • Implemented observability across multiple microservices using Honeycomb, improving issue detection by 40% and reducing mean time to resolution (MTTR) by 25%. • Developed a delete API for the data-translation service to remove pipelines from DynamoDB and clean up associated XSLT translator files from S3, reducing storage costs by 30%. • Added folder-prefix support in the file-store-manager service to streamline data organization within a single S3 bucket, cutting down the need for multiple dedicated buckets by 40%. • Worked under the direct mentorship of an SDE-IV, gaining valuable technical and architectural insights throughout the internship.