Vinod Bojedla

Built and operated AI infrastructure for LLM-powered applications, including model integrations, backend APIs, observability, cloud deployment, and production support. Developed Python and Java services and REST APIs connecting AI capabilities with existing platforms and downstream systems. Designed versioned, authenticated, validated, rate-limited APIs with backward-compatible contracts and service-level monitoring. Created reusable development/validation harnesses with mocks, replayable tests, local environments, and failure-injection to accelerate AI feature testing. Implemented AI telemetry for prompt/response traces, latency, token usage, cost, request volume, and failure categories. Improved release safety via staged rollouts (canary releases), regression validation, automated health checks, and fast rollback. Strengthened security with IAM/RBAC, least-privilege access, secret rotation, audit logging, environment separation, and controlled service-to-service communication. Manage

Built Python, Java, and Go backend services and REST APIs for production applications, distributed workflows, and cloud integrations. Developed asynchronous and event-driven services using Docker, Kubernetes, and queues to improve scalability and reliability. Automated build/test/deployment pipelines with Azure DevOps, Docker, and Kubernetes, reducing deployment time by 40%. Improved application performance through profiling, caching, database optimization, and service tuning, reducing query latency by 40%.

Built Java and Python services supporting high-volume financial applications with correctness, security, auditability, and production reliability requirements. Developed resilient event-driven systems using Kafka with asynchronous processing, retries, validation, queues, and downstream service integrations. Designed APIs and backend workflows with authentication, monitoring, robust error handling, and controlled recovery patterns for regulated production environments. Deployed containerized workloads to AWS EKS and Azure AKS via Jenkins-based CI/CD; supported production services through monitoring, incident response, and root-cause analysis.