Maneesh Ujji

About

IT Analyst/research background with hands-on experience deploying and hardening a multi-agent AI support/triage system (ticket ingestion + knowledge-base retrieval) with strong emphasis on reliability and observability. Has debugged real production issues spanning backend services and network latency (sync failures/partial writes) and is comfortable in Linux environments; also has academic exposure to robotics simulation and ROS2.

Experience

Education

Key Strengths

• Hardening multi-agent AI workflows with strict schemas, validation, retries, and escalation to prevent silent failures
• Productionizing services via containerization, dependency locking, and health checks to reduce environment-related issues
• Strong observability mindset (logging/health checks) to make systems debuggable and supportable
• End-to-end troubleshooting across application, backend services, and network layers (e.g., latency-induced partial writes)
• Customer-facing/on-site support: translating user issues into technical symptoms and feeding edge cases back into product improvements
• Building configurable Python systems to support customer-specific routing rules and response formats without destabilizing core code

Reference Highlights

• Strong ability to deploy and support complex systems in production
• Exceptionally fast learner
• Develops deep, practical understanding of new technologies
• Explains complex concepts clearly and intuitively
• Methodical debugger
• Highly organized; enables smooth team handoffs via logging
• Strong attention to detail
• Persistent in finding root causes
• Communicates findings clearly to the team
• Calm and focused under pressure
• De-escalates tense customer situations
• Strong customer communication; makes users feel supported
• Adaptable in fast-changing environments
• Translates operational needs into practical technical solutions
• Strong Python skills
• Comfortable with existing codebases and debugging