# Raveena Allam > Software Engineer @ Candid| SWE’25 | Software Engineer | SDET | Full Stack Web Developer Location: San Francisco Bay Area, United States Profile: https://flows.cv/raveena • Highly skilled Software Engineer proficient in a wide range of programming languages and technologies, including C#, C++, JavaScript, Java, C, and Python. Experienced in working with various databases such as MongoDB, Oracle, NoSQL, SQL, MySQL, Cosmo DB, and Server SQL, ensuring efficient data management. Proficient in utilizing powerful tools like OpenCV, Keras, TensorFlow, Scikit-Learn, NumPy, Pandas, and Matplotlib for data analysis and machine learning tasks. Familiar with web development technologies like HTML, CSS, JavaScript, Bootstrap, NodeJS, and jQuery, enabling the creation of interactive and responsive web applications. Experienced in REST API development and integration, connecting systems for seamless data communication. Skilled in utilizing popular software development tools like Git, PyCharm, Selenium, Jupyter Notebook, Postman, and more, streamlining the development process. Proficient in cloud environments, including AWS, Microsoft Azure, and Docker, for deploying cloud-native software solutions. Knowledgeable in data visualization and analysis, using Power BI and Python libraries to present insights in a clear and meaningful manner. Strong expertise in software testing methodologies, including Agile/Scrum and SDLC, ensuring the delivery of high-quality software products. Enthusiastic learner, continuously exploring new technologies and methodologies, committed to staying ahead in the ever-evolving software engineering landscape. With a proven track record of designing and implementing innovative software solutions, I am passionate about leveraging my technical skills and experience to drive excellence in software development. Let's connect and explore potential collaborations to create impactful solutions together! 👋 ## Work Experience ### Software Engineer @ Candid Jan 2022 – Present Architected & optimized cloud-native microservices using C# (.NET Core), ASP.NET Web API, and AWS Lambda, improving API response times by 35% and enabling 99.98% uptime. – Developed GraphQL-based APIs with LINQ & SQL Server, reducing over-fetching and improving query efficiency, cutting response times by 30%. – Built dynamic SPAs with React.js, Angular, and Next.js, integrating WebSockets & real-time event-driven updates, boosting user engagement by 40%. – Refactored authentication workflows using OAuth 2.0 & JWT, enhancing security and reducing unauthorized access attempts by 60%. – Implemented caching strategies with Redis & DynamoDB, accelerating query performance by 45% and reducing redundant database queries. – Automated CI/CD pipelines with Azure DevOps, Docker, and Kubernetes, reducing deployment failures by 50% and cutting release cycles by 30%. – Developed end-to-end testing suites with Selenium, Cypress, Jest, and Postman, increasing test coverage by 70% and reducing post-release defects. – Collaborated cross-functionally with UX/UI, DevOps, and data teams, leading initiatives that streamlined feature delivery, reducing time-to-market by 25%. ### Teaching Assistant @ California State University, Long Beach Jan 2021 – Jan 2022 I served as a teaching assistant for the "Computer Architecture and Organization" course, where I led lab sessions for a class of 101 students. During these sessions, we focused on digital design using Verilog on the Xilinx Vivado Platform. My responsibilities included guiding, teaching, and grading various projects, as well as providing feedback to improve students' understanding of hardware description language techniques. ### Graduate Research Analyst @ California State University, Long Beach Jan 2021 – Jan 2022 | Long Beach, California, United States I have experience in researching hardware, software, and cybersecurity topics, including CWE vulnerabilities and side-channel attacks. I have contributed to the development of a high-level ontology for malware and vulnerability analysis and have worked with various datasets and malware detection techniques. Additionally, I have worked on projects involving intelligent hardware-based anomaly detection and vulnerability analysis using machine learning and ontology modeling. I have also conceptualized storytelling visualization using PyQT5 GUI framework. In my work, I have benchmarked and assessed risk using failure modes and effect analysis of hardware performance counters in vulnerability analysis. Additionally, I have implemented a system-level ontology for CWE-Attack Impacts and malware attacks on system and hardware components to improve detection and prevention. CWE-Attack Impacts and Malware attacks on systems and hardware components. CWE-Attack Impacts and Malware attacks on systems and hardware components. ### Software Engineer Intern @ Grepthor Software Solutions Jan 2019 – Jan 2019 As a project at Grepthor Software Solutions- Developed and streamlined service and application pipelines using Python for data processing and metric tracking. Designed scalable deployment architectures using Kubernetes and Cassandra, ensuring reliable service delivery. Reduced latency by 30% using Kafka message queues for distributed data processing. Managed pods, scaled resources, and implemented container orchestration with Kubernetes for optimal performance and high availability. Skills: Microservices, Apache Kafka, Cassandra, Kubernetes, Python ## Education ### Master of Science - MS in Computer Science California State University, Long Beach ### Bachelor of Technology - BTech in Computer Science GITAM Deemed University ### Intermediate in MPC Ascent Junior College ## Contact & Social - LinkedIn: https://linkedin.com/in/raveena-allam --- Source: https://flows.cv/raveena JSON Resume: https://flows.cv/raveena/resume.json Last updated: 2026-04-11