Saurabh Ranjan

Serve as forward-deployed AI systems architect for strategic enterprise and government partners, including Google, IBM, HPE, Delhi State Government, and Central Government agencies owning end-to-end technical delivery, architectural decisions, and stakeholder alignment across AI, security, and cloud platforms in regulated environments. Lead execution of AI-enabled systems from ambiguous requirements through production deployment, making risk-aware architectural decisions that balance performance, security, compliance, and operational constraints while maintaining direct accountability for delivery outcomes in complex, multi-party environments. Drive client engagement through technical demonstrations, solution documentation, presales architecture, and knowledge transfer activities creating architectural artifacts and reference implementations that accelerate adoption across stakeholder teams. Establish and enforce production-readiness standards, release governance, and quality guardrails to ensure deployed systems remain reliable, auditable, and maintainable beyond initial rollout.

Led a cross-functional engineering team of 18 members spanning backend, frontend, DevOps, QA, and cybersecurity sprint planning, resource allocation, performance reviews, and cross-team coordination while maintaining hands-on technical contributions. Architected and delivered an AI-driven cybersecurity monitoring platform covering threat detection, compliance workflows, DLP, and vulnerability mitigation reducing manual threat analysis effort by 50% while ensuring auditability, explainability, and enterprise security controls in regulated environments. Led presales architecture and solution design, producing solution documents, POCs, and system blueprints to translate complex security problems into deployable AI-enabled solutions and de-risk adoption within security-critical workflows.

Led a team of 5 developers across backend and frontend in designing and implementing IRCTC CyberX, a cloud-native anti-fraud platform for Indian Railways managing technical mentorship, code review, and work allocation while improving fraud prevention outcomes by 40%. Collaborated directly with government anti-fraud units and operations teams to gather requirements, prioritize features, and ensure system scalability, high availability, and secure AWS deployment in a mission-critical environment. Maintained quality standards through code reviews and testing protocols while remaining hands-on with architecture and critical implementation paths, coordinating technical discussions and facilitating cross-functional alignment.

Built Blaze Deploy, a SaaS platform automating Salesforce configuration deployments, cutting deployment errors by 90% and accelerating release cycles for enterprise clients. Developed STELA, integrating surgical mapping data with Smith+Nephews LMS to improve clinical efficiency and procedural accuracy in regulated healthcare environments.

Maintained and enhanced an internal financial training and management platform, improving system reliability and consolidating user data for informed decision-making. Improved front-end performance by reducing load times and introducing modular components to support maintainability and future enhancements.