Senior / Staff / Principal Software Engineer
Secure systems · Agentic AI infrastructure · Platform engineering · Mobile

micrantha.com · ryanjennin.gs · email

I build long-lived software systems where correctness, security, operability, and explicit trust boundaries matter.

My background spans 15+ years across Android, iOS, React Native, Kotlin Multiplatform, backend systems, cloud/platform engineering, infrastructure, and application security. I still work across the stack, but my current focus is the intersection of agentic AI, secure software delivery, platform engineering, and governance.

The recurring question behind much of my current work is:

How do autonomous systems become more capable without quietly accumulating unchecked authority?

• Governed agentic systems — policy, capabilities, approvals, evidence, provenance, replay, and bounded side effects.
• AI-native SDLC — treating agents as constrained delivery participants rather than trusted autocomplete or autonomous maintainers.
• Context integrity — deterministic prompt/context composition, manifests, lockfiles, provenance, and reproducible agent inputs.
• Agent identity & authorization — sender-constrained OAuth, proof-of-possession, replay resistance, and MCP security boundaries.
• Local-first AI infrastructure — model routing, supervisor/specialist agents, memory, evaluation, scheduling, and secure execution on self-hosted infrastructure.
• Platform & developer experience — paved paths, strong contracts, predictable failure modes, observability, CI/CD, and incremental modernization.

A principle I keep returning to: a system may propose its successor, but it should not independently authorize the transition to that successor. Durable state changes need an external trust boundary and evidence that can be independently evaluated.

A set of deliberately separated projects exploring those boundaries:

flowchart LR
    C["Calathea<br/>—<br/>workflow"] --> I["Invokrum<br/>—<br/>context identity"]
    I --> D["Dubnium<br/>—<br/>bounded execution"]
    D --> K["Keylix<br/>—<br/>sender binding"]
    K --> A["Anthesis<br/>—<br/>policy · approval · evidence"]
    A --> E["Governed effects"]

The goal is not a monolithic agent framework. The interesting work is at the boundaries: what context entered the system, who or what is acting, what authority it has, what effect is requested, who approves it, and what evidence remains afterward.

• Anthesis Governance Lab — public conformance and demonstration surface for deterministic agent-governance contracts.
• Secure Agent Workflows — practical patterns, threat models, task contracts, and evidence expectations for secure AI-assisted software delivery.
• Eyespie — Kotlin Multiplatform / mobile computer-vision work, including iOS and MediaPipe integration.
• Guitar Practice System — structured practice tooling exploring progression, assessment, backing tracks, and AI-assisted music workflows.
• git-autocommit and other small tools — experiments in developer workflow automation, repository safety, and bounded automation.

There is also a fair amount of older code here. I started programming in 1998 and publishing open-source software before GitHub existed; not every repository represents my current engineering style or priorities. The projects above are the useful signal.

I tend to work best on systems that are already real enough to have constraints:

• production software with users, migrations, compatibility requirements, and operational history;
• security-sensitive authentication, authorization, credential, and trust boundaries;
• platform or developer-experience work that must improve delivery without creating a second platform nobody wants to maintain;
• mobile systems where platform-specific behavior matters and cannot always be abstracted into "just another web client";
• agentic/AI systems where probabilistic reasoning needs deterministic controls around consequential effects.

I prefer incremental modernization over rewrites, explicit contracts over convention, boring cryptography over clever cryptography, and evidence over claims that a system "should" be safe.

I am continuing to turn the Micrantha work into small, composable, auditable systems and public reference material for secure agentic software delivery.

Professionally, I am interested in Staff / Principal engineering and selective contract work around AI infrastructure, platform engineering, application security, developer experience, secure SDLC, and complex mobile/backend systems — preferably remote-first in Canada.

I am also interested in collaborating on work around:

• agent governance, authorization, observability, and evaluation;
• MCP and agent/tool security;
• secure platform and API design;
• mobile security and device/app trust;
• local/self-hosted AI infrastructure;
• practical research-to-production engineering.

I play guitar and piano, record music, play hockey, and occasionally turn engineering energy toward things that have nothing to do with infrastructure — including The Fatherless, a long-form fiction/screenplay project.

_{he / him}