Best-fit role
AI Systems Engineer
Best fit for work that combines backend services, workflow automation, infrastructure, and AI-enabled product logic into one operating system.
Experience & Skills
This page shows the background behind the portfolio: backend engineering, infrastructure automation, cloud delivery, security work, applied AI systems, and current graduate study in artificial intelligence.
The strongest fit is work where backend platforms, workflow automation, infrastructure, and AI-enabled product logic need to ship together as one system.
Best-fit role
Best fit for work that combines backend services, workflow automation, infrastructure, and AI-enabled product logic into one operating system.
Best-fit role
Strongest when AI is part of a grounded workflow such as retrieval, guided intake, summarization, or decision support.
Best-fit role
Comfortable owning the APIs, deployment workflows, cloud infrastructure, and operational tooling that keep products reliable.
Roles across consulting, enterprise engineering, infrastructure, security, and application development that support systems-focused AI work.
Sole engineer responsible for the full delivery lifecycle of accessible web systems for nonprofit organizations: architecture, frontend, infrastructure, deployment, and ongoing operational support.
Highlights
Stack and Tools
Short-term contract focused on enterprise API integration support: testing, validation, troubleshooting, and cross-team coordination for internal system workflows.
Highlights
Stack and Tools
Owned infrastructure automation and cloud application delivery across AWS environments: provisioning, configuration management, microservice development, and operational tooling.
Highlights
Stack and Tools
Owned application-level security hardening across internal web applications: vulnerability remediation, secure API design, and authentication enforcement.
Highlights
Stack and Tools
Built and maintained frontend and service-layer software for internal retail systems at enterprise scale: cross-repo modernization, microservice development, and cross-team delivery.
Highlights
Stack and Tools
Developed and maintained e-commerce and inventory management software.
Highlights
Stack and Tools
Analyzed space physics data and contributed to published research on Ultra-Low-Frequency Wave Investigations.
Highlights
Stack and Tools
Current stack organized around applied AI systems, backend and platform engineering, cloud infrastructure, and production delivery.
Working Style
Additional
Where the stack is going deeper right now as the work moves further toward AI systems and platform engineering.
Grounding AI-assisted products in retrieved context so the system stays useful, inspectable, and easier to trust.
Designing intake, triage, and guided interaction systems where AI supports the workflow without owning every decision.
Improving how AI-backed software validates outputs, compares behavior over time, and avoids demo-only quality.
Building the queues, APIs, persistence, and task routing layers that make AI features behave like maintainable software.
Academic work that supports the applied systems and AI focus of the portfolio.
Focusing on applied AI, cloud computing, and machine learning.
Built a strong foundation in computer science fundamentals, mathematical reasoning, and physical sciences.
Credentials that support the infrastructure and cloud side of the work.