TypeScript
Python
React
GCP
NestJS
Navigating Toward
AI-Driven Engineering
0
Years of Experience
▲ Currently accelerating
Current Gear
ARCHITECT
● Current Destination
Software Engineering Architect
- Build and present AIDE (AI Document Extractor) to the entire Egen organization — an AI engine that reads patient document packages, splits and categorizes pages, and replaces 2-4 hours of manual processing per package. Build an evaluation pipeline using real production data as a gold standard, benchmark multiple AI models head-to-head across 30 real-world packages, and optimize through three levers: prompt engineering, model selection, and supervised fine-tuning. Live in production with continuous learning from human review feedback, eliminating the need for 2 FTEs while enabling scalability to millions of documents per year, dramatically reducing turn-around time for order completion, and ensuring standardized categorization across every document.
- Author 17 custom agentic skills for OpenCode automating engineering workflows — from JIRA story execution to production debugging to E2E test generation — saving hours of repetitive context-switching daily.
- Architect a multi-agent orchestration system using Google Agent Development Kit, where specialized agents collaborate autonomously to complete complex multi-step tasks.
- Built a multi-agent construction planning app as part of a Google ADK workshop — domain-specific agents (construction builder, electrician, goods vendor, plumber, carpenter) communicate autonomously to produce a coordinated construction plan.
- Design and present “AI-Powered Engineering Workflows” to the team — a system of 6 specialized AI agents (Manager, Architect, Product, Developer, Designer, Support) spanning the full software lifecycle across Plan, Build, Test, Ship, and Operate phases, connected to 12 systems (Jira, GitHub, Concourse, GCP, 3 production databases, Google Workspace, Zephyr, Depcom) and 6 codebases, with built-in guardrails for PHI protection, branch safety, credential security, and human-gated approvals at every stage.
- Reduce production incident investigation from 30–60 minutes of manual work across multiple tools to ~2 minutes through the AI Support agent that correlates GCP logs, database queries, and recent deployments into a single root-cause summary.
- Manage 9 engineers across 4 teams as a manager of managers — overseeing a mix of managers, leads, senior engineers, and engineers — conducting monthly 1:1s and annual performance reviews, maintaining a ~90% retention rate through mentorship, career development, and a culture of high-quality code and best practices that strengthens Egen’s brand value and drives revenue growth.
- Define technical direction for the OPUS platform — owning architecture decisions across microservices, data contracts, and cross-team integration patterns.
- Lead architecture review sessions and design discussions, establishing standards for API design, service boundaries, and data modeling across the engineering organization.
- Evaluate and introduce emerging technologies — assessing build-vs-buy trade-offs, prototyping proof-of-concepts, and presenting technical recommendations to leadership.
- Drive engineering productivity initiatives by identifying bottlenecks in the development lifecycle and implementing tooling, automation, and process improvements.
- Collaborate with product management and clinical stakeholders to translate business requirements into scalable technical solutions aligned with HIPAA and healthcare compliance standards.
- Establish and enforce coding standards, documentation practices, and engineering best practices through architectural decision records (ADRs) and technical governance.
2 FTEs automated
6 AI agents
17 AI skills built
4,500 lines domain knowledge
12 systems connected
9 engineers
~90% retention rate
4 teams