MSc Thesis Residency, Exploring distributed agent-based AI orchestration frameworks as scalable software automation approaches for life sciences applications.

Matured my previous kubernetes services, improving simulation testing, metrics, logging and moved application level config to service level config - generalised for different factory systems. Improved reliability by creating backoff systems for external systems. Steered a new integration with IBM Maximo, structured for easy extension and integration with future systems. Developed generalised Canary for IQ/OQ testing of any REST API given its OpenAPI spec with load testing included - reducing dev time significantly.

Developed cloud platform for delivering AI analysis applications for investment fund managers. Leveraged Azure, Docker and Terragrunt to build and deploy a containerized microservices architecture that processes news, transcripts and market data for faster analyst research loop.

Following on from intern work, developed microservices to align different MES/OMS systems for a new Inspection platform and worked on a Local Machine Integration to interact with machines behind ICE network.