{ "$schema": "https://jsonresume.org/schema/", "generatedAt": "2026-09-19T11:35:56.028Z", "basics": { "name": "Mayank Manas", "label": "Backend SDE-2 · Java, Spring Boot, AWS", "headline": "Backend engineer (5+ YOE) building release infrastructure and AI-assisted engineering tooling for enterprise security products. I work on the systems that decide what ships, how it's validated, and how it's kept secure.", "email": "iammayank.manas@gmail.com", "phone": "+91-8700833759", "availability": "Open to backend and infrastructure roles", "location": { "city": "Delhi NCR", "region": null, "country": "India" }, "url": "https://mayankmanas.pages.dev", "profiles": [ { "network": "GitHub", "username": "mayankmanas", "url": "https://github.com/mayankmanas" }, { "network": "LinkedIn", "username": "mayankmanas", "url": "https://www.linkedin.com/in/mayankmanas/" } ] }, "work": [ { "company": "Coriolis Technologies", "position": "SDE II", "location": "India", "startDate": "2021-07", "endDate": null, "summary": "Engineering and release infrastructure for Imperva's database auditing Agent — a component installed on database servers and hosts to audit, monitor and secure database activity.", "workstreams": [ { "name": "Internal Data Coverage & Compatibility Platform", "tech": [ "Java 8", "Spring Boot", "MySQL" ], "highlights": [ "Designed and developed the Internal Data Coverage Tool (IDCT), a Java 8, Spring Boot and MySQL platform used by ~40 engineers across 3 teams to manage Agent compatibility across ~300 OS/DB combinations and ~10,000 configuration permutations.", "Architected the data model, backend APIs and UI to represent and manage multi-dimensional compatibility across OS/DB versions, Agent modes, database configurations, encryption modes and other supported dimensions.", "Own the integration of the compatibility platform with the OS/DB support release pipeline, mapping support progression from development and certification through automation testing and final release coverage.", "Own Agent compatibility coverage, serving as the focal point for determining supported configurations, tracking coverage changes and history, and maintaining accurate OS/DB compatibility information through the release lifecycle." ] }, { "name": "Agent Release Infrastructure", "tech": [ "Java", "Linux", "Windows", "GDB" ], "highlights": [ "Developed features for a Java-based remote execution service within the Agent testing platform, exposing APIs used by automation workflows to execute operations on remote Linux and Windows test machines.", "Developed a cross-platform core-dump diagnostics API that remotely retrieves crash dumps, processes them using native GDB, and returns structured diagnostic information including failure details, memory and heap information, and timestamps for developer debugging.", "Developed and maintained Java-based utilities and supporting services powering the Agent testing platform, implementing feature enhancements and resolving defects across the system.", "Owned a 28-day monthly Agent release cycle, coordinating validation across ~700 test environments, triaging failures, communicating defects with upstream development teams, and verifying fixes through subsequent test runs." ] }, { "name": "AI-Assisted Engineering", "tech": [ "Python", "Google ADK", "Amazon Bedrock", "Browser Automation" ], "highlights": [ "Developed and deployed Python-based AI agents using Google ADK and Amazon Bedrock to automate release validation and Agent compatibility workflows used by engineering teams.", "Built an AI-powered release task validator that generates expected release permutations using OS/DB Cartesian products, applies maintained exclusions and support-date constraints, and compares expected coverage against release tasks to identify missing permutations.", "Developed a vendor compatibility agent that dynamically discovers and extracts OS/DB compatibility from vendor documentation and web-based compatibility matrices using web crawling and browser automation, classifies findings for human verification, and generates bulk compatibility updates through backend APIs.", "Implemented human-in-the-loop safeguards and persistent vendor-source context for compatibility discovery, requiring user validation before modifying compatibility data while retaining verified vendor sources for subsequent analysis." ] }, { "name": "File Tokenization & Encryption Proxy", "tech": [ "Java", "AWS S3", "Azure", "IBM COS", "SFTP" ], "highlights": [ "Engineered file tokenization and encryption pipelines for enterprise systems, supporting stream and field-level encryption in Java across diverse file types and storage systems.", "Designed multi-cloud data protection across AWS S3, Azure, IBM COS and SFTP, enabling secure handling of sensitive data across heterogeneous customer environments.", "Implemented RBAC and multi-tenancy to provide fine-grained access control and scalable tenant isolation for enterprise deployments." ] }, { "name": "SaaS Metrics & Resource Usage Platform", "tech": [ "Kubernetes", "Metrics Pipelines" ], "highlights": [ "Built a resource tracking and optimization platform for SaaS deployments, collecting pod-level metrics across customer environments to guide resource allocation and scaling.", "Enabled data-driven resource allocation, reducing customer cloud infrastructure costs by ~11%." ] }, { "name": "REST API Based Encryption / Masking Service", "tech": [ "Spring Boot", "REST" ], "highlights": [ "Developed a secure Spring Boot microservice exposing REST APIs for encryption, decryption and data masking, with unit, integration and end-to-end test coverage." ] }, { "name": "Dynamic Configuration Management System", "tech": [ "Java", "Distributed Systems" ], "highlights": [ "Developed a configuration management system for distributed services, enabling dynamic cluster configuration and runtime resolution.", "Reduced deployment and service boot-up times by ~30% through dynamic configuration management." ] }, { "name": "Performance Benchmarking Tool", "tech": [ "GitHub Actions" ], "highlights": [ "Developed and automated a GitHub Actions-based benchmarking system to compare deployment performance across branches and releases and detect performance regressions early." ] } ] } ], "education": [ { "institution": "Chitkara University", "degree": "B.E. Computer Science Engineering", "startDate": "2017-07", "endDate": "2021-06", "score": "CGPA 9.3", "awards": [ "Scholar award for being in the top 1% of graduates" ] } ], "skills": [ { "group": "Programming Languages", "priority": "primary", "keywords": [ "Java", "Python", "JavaScript" ] }, { "group": "Backend", "priority": "primary", "keywords": [ "REST APIs", "Microservices", "WebSockets", "OpenAPI", "Event-Driven Architecture", "Remote Execution" ] }, { "group": "Frameworks", "priority": "primary", "keywords": [ "Spring Boot", "Spring Cloud", "Google ADK", "Playwright", "Selenium" ] }, { "group": "AI & LLM", "priority": "primary", "keywords": [ "Amazon Bedrock", "Google ADK", "AI Agents", "LLM-based Workflow Automation" ] }, { "group": "Cloud", "priority": "primary", "keywords": [ "AWS EC2", "AWS S3", "AWS Lambda", "AWS IAM", "AWS ECS", "AWS SQS", "AWS ELB" ] }, { "group": "Design", "priority": "primary", "keywords": [ "Data Structures & Algorithms", "LLD", "HLD", "Distributed Systems", "Database Schema Design" ] }, { "group": "Databases", "priority": "secondary", "keywords": [ "MySQL", "NoSQL", "Elasticsearch" ] }, { "group": "Containerization", "priority": "secondary", "keywords": [ "Docker", "Kubernetes" ] }, { "group": "CI/CD", "priority": "secondary", "keywords": [ "GitHub Actions" ] }, { "group": "Monitoring & Logging", "priority": "secondary", "keywords": [ "Kibana", "Prometheus", "Grafana" ] }, { "group": "Queues", "priority": "secondary", "keywords": [ "Kafka Streams" ] }, { "group": "Security", "priority": "secondary", "keywords": [ "JWT", "RBAC", "OAuth2", "Data Encryption", "Data Masking" ] }, { "group": "Performance", "priority": "secondary", "keywords": [ "Caching", "Load Balancing", "JVM Performance Tuning", "Thread Dump Analysis", "GDB" ] } ], "projects": [ { "name": "FileServer", "blurb": "Secure HTTPS file server for LAN environments — streaming I/O for files up to 100 GB, path-traversal defense, IP whitelisting and structured logging.", "stack": [ "TypeScript", "Node.js", "Express", "Jest" ], "slug": "fileserver", "highlights": [ "Streams files up to 100 GB without buffering", "HTTP Basic Auth with bcrypt, RFC1918 IP whitelist, rate limiting", "Winston structured JSON logging with rotation; jest + supertest coverage" ], "links": { "repo": "https://github.com/mayankmanas/FileServer", "demo": null }, "caseStudy": "https://mayankmanas.pages.dev/projects/fileserver" }, { "name": "BFS/DFS Visualizer", "blurb": "React application for visualizing graph traversal and node exploration in a grid-based system.", "stack": [ "React", "JavaScript" ], "highlights": [], "links": { "repo": null, "demo": null }, "caseStudy": null }, { "name": "Exercise Tracker", "blurb": "Full-stack activity logging application with a React frontend and a Node/Express API.", "stack": [ "React", "Node.js", "Express", "MongoDB" ], "highlights": [], "links": { "repo": null, "demo": null }, "caseStudy": null } ] }