Kiran Krishna — Melbourne-based senior AI engineer and AWS architect with 14+ years across government, transport, rail, AWS cloud platforms, and agentic systems. Currently leading agentic AI delivery at the Department of Transport and Planning Victoria.
I'm Kiran Krishna, a Melbourne-based senior AI engineer and AWS architect with over a decade of experience across enterprise software, cloud platforms, transport, rail, and public-sector technology.
My current work focuses on production-grade agentic AI: systems that use tools, coordinate specialist agents, preserve auditability, respect approval boundaries, and operate within real enterprise constraints.
I've also architected cloud-native AWS platforms, industrial software systems, and automation patterns for complex, highly regulated environments. Outside work, I build personal AI systems, open-source agent tooling, and learning resources that help me test emerging patterns before applying them in enterprise delivery.
An enterprise agentic AI platform: a reusable, governed agent runtime that separates the agent layer from domain skills, so business areas automate document-heavy, governance-sensitive workflows on shared infrastructure — with orchestration, traceability, guardrails, and human oversight built in.
◆ Reusable runtime for org-wide automationWhere I test agent patterns end to end. Jarvis OS — a local-first personal AI operating system routing a primary agent to specialists, with memory and approval-gated tools. AgentCouncil — an open-source Claude Code MCP plugin for structured multi-agent deliberation.
★ Open source · multi-agent runtime testbedA secure, multi-account AWS foundation on Control Tower and Landing Zone Accelerator — centralized networking and auditing, standardized guardrails and governance, SSO + CyberArk via IAM Identity Center, and SOC/SIEM security monitoring — giving teams a governed, compliant platform to build on.
▲ Secure, compliant multi-account foundationCloud-native industrial-IoT applications on AWS for rolling-stock and locomotive health: real-time, fleet-wide health monitoring, an image ingestion & search system for fault analysis, and streaming sensor analytics across edge and cloud — serving global rail operators.
▲ Fleet-wide operational visibilityA free platform I built to teach building AI agents — from fundamentals to the frontier. Structured courses across agentic AI, Claude Code, Codex, AI leadership, and Amazon Bedrock AgentCore — read or listen, with slide decks, hands-on labs, and quizzes. No signup, no paywall.
Leading enterprise AI and cloud-platform initiatives in a public-sector environment. Focused on governed agentic AI, reusable automation patterns, secure AWS foundations, LLMOps, guardrails, auditability, and stakeholder-aligned delivery.
Architected cloud-native and industrial-IoT systems for rail and transport platforms, including real-time monitoring, edge-to-cloud workflows, image and data ingestion, observability, and AWS migration patterns.
Led Java/J2EE platform delivery for enterprise transport systems, spanning requirements analysis, solution design, backend development, production support, mentoring, and modernization initiatives.
Working on an agentic system, an AI platform, or enterprise AI delivery? Drop a note — I read everything.
