Karthikeya H S

Software Engineer

Bengaluru, Karnataka, India6 yrs 5 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in backend development and cloud computing.
Proven track record in migrating large-scale services to AWS.
Strong mentor and collaborator in engineering teams.

Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in SaaS and cloud-based solutions.

Contact

karthikeyahs@gmail.com LinkedIn

Skills

Core Skills

AwsSpring BootSamlCi/cdDeep Learning

Other Skills

AlgorithmsAmazon EKSAmazon Relational Database Service (RDS)AngularAngularJSAntApplied Machine LearningArtificial Intelligence (AI)C (Programming Language)C++CommunicationComputer ScienceComputer networksData StructuresDatabase Design

About

I am a Software Engineer - II with experience in backend development, distributed systems, and cloud computing. My technical expertise includes Java, Python, Spring Boot, AWS (EC2, RDS, S3), MySQL, Redis, and MongoDB. At Cisco, I have contributed to migrating large-scale services to AWS, improving scalability and reducing operational costs, and to building fault-tolerant applications. I have also worked extensively on software quality and reliability, including refactoring with design patterns, increasing unit test coverage with JUnit, and resolving critical escalations under tight SLAs. I enjoy collaborating with teams, mentoring peers, and ensuring that systems are both scalable and maintainable. I completed my M.Tech in Software Systems (BITS Pilani), with coursework in Cloud Computing, Distributed Systems, Applied Machine Learning, Deep Learning, Natural Language Processing and Advanced Statistics. Beyond work, I continue to learn and explore new technologies to strengthen my ability to solve complex engineering problems at scale.

Experience

6 yrs 5 mos

Total Experience

3 yrs 2 mos

Average Tenure

4 yrs 10 mos

Current Experience

Cisco

3 roles

Software Engineer III

Aug 2025 – Present · 10 mos

Software Engineer II

Promoted

Oct 2023 – Aug 2025 · 1 yr 10 mos

Collaborated on redesigning the deployment of Cisco Secure Email Encryption Service (CSEES) application servers (EC2), Object Storage (S3) and MySQL (Amazon RDS) during the migration to AWS, which improved scalability and reduced operational costs.
Contributed to the deployment of a RESTful Spring Boot application on AWS EC2 for encrypted email delivery via Microsoft Graph API, enabling horizontally scalable throughput of 5,000+ emails/hour.
Developed unit tests using JUnit, increasing code coverage.
Refactored legacy code using multiple design patterns, improving maintainability and reducing code smells significantly, as evidenced by SonarQube metrics.
Handled multiple customer escalations, achieving an average resolution time of 4 hours and ensuring minimal impact on production.
Mentored interns and junior engineers through design and code reviews, fostering best practices in large-scale system design, distributed architecture, and onboarding efficiency.

AWSSpring BootMySQLEC2S3Distributed Systems+3

Software Engineer

Aug 2021 – Oct 2023 · 2 yrs 2 mos

Implemented enterprise-grade SAML 2.0 Single Sign-On (SSO) using OpenSAML, integrating with customer IAM providers and adopted by 35% of customers to enhance security and reduce password reliance.
Optimized CI/CD pipelines by refining Ant builds, significantly reducing build time from 3 hours to just 30 minutes.
Collaborated with cross-functional teams to ensure seamless integration and deployment of email encryption solutions at Cisco.

SAMLOpenSAMLCI/CDAntEmail Encryption

Indian institute of technology, delhi

Research Intern

May 2019 – Jul 2019 · 2 mos · New Delhi Area, India

Conducted research on deep learning applications for the rational design of oxide glasses, analyzing over 100,000+ oxide glass compositions (37 components) to predict eight key material properties.
Developed predictive models using Python, Scikit-Learn, and GPytorch, enhancing prediction accuracy by 15%.
Co-authored a published paper in Materials Horizons, contributing to advancements in material science.

Deep LearningPythonScikit-Learn