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Senior software engineer with 8+ years of experience building and operating production systems across enterprise platforms, intelligent business automation, and financial technology. Experienced in scalable backend services, data pipelines, and cloud-native infrastructure using Python, SQL, Docker, Kubernetes, and AWS. Known for pragmatic problem solving, production-quality engineering, and clear communication with product and business stakeholders to translate complex requirements into reliable, maintainable solutions. Also mentors engineers on repeatable delivery practices and production operations/observability for ML and data systems.…Senior software engineer with 8+ years of experience building and operating production systems across enterprise platforms, intelligent business automation, and financial technology. Experienced in scalable backend services, data pipelines, and cloud-native infrastructure using Python, SQL, Docker, Kubernetes, and AWS. Known for pragmatic problem solving, production-quality engineering, and clear communication with product and business stakeholders to translate complex requirements into reliable, maintainable solutions. Also mentors engineers on repeatable delivery practices and production operations/observability for ML and data systems.

Harish Ravi

Software Engineer, DevOps Developer, Data Engineer, +2

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Senior software engineer with 8+ years of experience building and operating production systems across enterprise platforms, intelligent business automation, and financial technology. Experienced in scalable backend services, data pipelines, and cloud-native infrastructure using Python, SQL, Docker, Kubernetes, and AWS. Known for pragmatic problem solving, production-quality engineering, and clear communication with product and business stakeholders to translate complex requirements into reliable, maintainable solutions. Also mentors engineers on repeatable delivery practices and production operations/observability for ML and data systems.…Senior software engineer with 8+ years of experience building and operating production systems across enterprise platforms, intelligent business automation, and financial technology. Experienced in scalable backend services, data pipelines, and cloud-native infrastructure using Python, SQL, Docker, Kubernetes, and AWS. Known for pragmatic problem solving, production-quality engineering, and clear communication with product and business stakeholders to translate complex requirements into reliable, maintainable solutions. Also mentors engineers on repeatable delivery practices and production operations/observability for ML and data systems.

Available to hire

Senior software engineer with 8+ years of experience building and operating production systems across enterprise platforms, intelligent business automation, and financial technology. Experienced in scalable backend services, data pipelines, and cloud-native infrastructure using Python, SQL, Docker, Kubernetes, and AWS.

Known for pragmatic problem solving, production-quality engineering, and clear communication with product and business stakeholders to translate complex requirements into reliable, maintainable solutions. Also mentors engineers on repeatable delivery practices and production operations/observability for ML and data systems.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Beginner

Work Experience

Senior Software Engineer at Accenture

August 1, 2023 - Present

Designed and deployed production machine learning services on AWS using Docker and Kubernetes to support high-volume inference with improved reliability and scalability. Built end-to-end MLOps pipelines for model training, versioning, monitoring, and automated deployment to reduce manual effort and increase release frequency across multiple teams. Developed deep learning models using PyTorch and TensorFlow for document understanding and workflow automation, improving business-critical processing accuracy. Engineered scalable data pipelines with SQL, Apache Spark, and Airflow to ingest, transform, and serve data for downstream ML training and analytics. Implemented REST APIs and backend integrations to expose predictions to internal and third-party platforms for real-time decision support. Optimized inference latency through profiling, container tuning, and caching; established observability and model monitoring for drift/anomaly detection. Automated CI/CD pipelines using Infrastructure

Senior Software Engineer at IBM

March 1, 2020 - August 1, 2023

Built and maintained production machine learning services for intelligent business automation, financial insights, and document understanding using Python, TensorFlow, and PyTorch. Developed scalable data pipelines with SQL, Spark, and Airflow for feature engineering, training, and batch inference. Containerized ML workloads with Docker and orchestrated on Kubernetes to improve consistency and horizontal scalability. Implemented model versioning and monitoring for performance tracking, drift detection, rollback, and support for A/B testing. Designed and exposed REST APIs for model inference and business rule execution to integrate with customer-facing applications and internal decision workflows. Optimized inference latency and throughput by refactoring serving code, tuning batch sizes, and using asynchronous processing for high-volume workloads. Contributed to technical design and code reviews to improve maintainability and adherence to best practices. Implemented CI/CD for automated

Software Engineer at Crescent Financial Systems

July 1, 2018 - March 1, 2020

Developed and maintained financial technology platforms focused on automation, risk reduction, and operational visibility using Python, SQL, and REST APIs. Built ETL and data processing workflows to improve data quality and reliability for internal tooling and business users. Implemented backend services and integrations supporting decision support and business process improvements across financial operations. Containerized applications with Docker and deployed to cloud infrastructure to improve environment consistency and simplify deployment. Automated manual workflows and reporting to reduce operational effort and improve accuracy. Collaborated with engineers and business stakeholders to gather requirements and resolve delivery challenges; supported production by diagnosing and resolving incidents and improving system reliability and user trust.