Koushik Anitha Raja

Koushik Anitha Raja is a cloud-native systems engineer whose early-career trajectory shows an unusually clear focus: building data-intensive platforms and integrating AI capabilities into real production workflows without compromising governance, security, or reliability. With 3+ years of professional experience since 2023, Koushik has worked across enterprise financial systems, AI-enabled analytics, ML observability infrastructure, and real-time distributed platforms—consistently operating where correctness and scalability are decisive.

At Microsoft, Koushik serves as a Software Engineer II on the FDE Planning Core (Fusion Framework), contributing to a mission-critical financial planning and forecasting platform that supports enterprise budget cycles and forecasting processes across large internal user populations. His work targets the core engineering concerns that determine whether such systems remain dependable during peak planning windows: performant data workflows, robust stored-procedure logic, tenant-level security enforcement, and audit-ready controls that protect both data integrity and enterprise trust.

In parallel, Koushik contributes to the Fusion AI Finance Agent Ecosystem, engineering AI-enabled interfaces that allow finance users to interact with complex datasets using natural language while preserving enterprise governance. His work includes building Model Context Protocol (MCP) clients and servers, orchestrating AI workflows that can dynamically generate SQL, DAX, and OLAP queries, and delivering conversational interfaces in developer and web environments—enabling self-service analytics and reducing cycle time for analysis and reporting.

Prior to Microsoft, at Turing, Koushik built components of a large-scale ML observability platform—combining high-frequency telemetry ingestion, real-time metric aggregation, and integrated monitoring stacks. He delivered both user-facing dashboards and backend microservices, strengthened caching and async processing, and integrated standard observability tooling (ELK, Prometheus, Grafana) to improve debugging efficiency and transparency into model performance at scale. He also architected an LLM integration gateway for Google’s Gemini API usage across products, implementing batching/caching/resilience patterns, standardized schemas, structured logging, and operational monitoring to keep inference fast and stable under load.

Earlier, at Green Action Studio, Koushik helped build customer-facing and internal systems for distributed mobility operations using event-driven microservices and serverless infrastructure—implementing Kafka pipelines, dashboards, and AWS CDK/Lambda-based monitoring for uptime and deployment efficiency. His earliest industry experience at IIT Hyderabad included building workflow automation platforms, database optimizations, caching layers, and Docker-driven CI/CD to replace fragmented manual processes with a maintainable system.

Taken together, Koushik’s profile reflects a modern engineering identity: cloud-native platform delivery, data correctness and security discipline, and AI integration engineered as a reliable product capability—not a demo.