Salesforce Platform Engineer | Software and Cloud Systems | Applied AI
I connect business context with disciplined engineering to build systems teams can rely on. My work spans requirements, architecture, implementation, validation, release, and production support.
Portfolio | LinkedIn | Trailblazer | Email
| System | Engineering focus | Evidence |
|---|---|---|
| Enterprise CPQ modernization | Salesforce CPQ, Apex, LWC, MuleSoft, CI/CD, Selenium | 25% faster quote cycle, three defect-free releases, 35% fewer production incidents |
| AstraNode | GraphRAG architecture, citation-grounded retrieval, Neo4j, FastAPI, React | 608 NASA publications processed in 48 hours; NASA Space Apps local winner |
| Streaming graph pipeline | Kafka, Kubernetes, Neo4j, Docker, graph algorithms | 3.6M records streamed with the query layer preserved across deployment models |
| Elastic face recognition | AWS IaaS, SQS, EC2, Flask, PyTorch, custom autoscaling | 100% accuracy across a 1,000-image workload; scaled from 0 to 15 workers |
- Salesforce platform: Apex, LWC, CPQ, Flow, SOQL, Agentforce, CRM architecture
- Applied AI and data: Python, RAG, evaluation, PyTorch, Neo4j, pandas
- Software and cloud systems: AWS, Docker, Kubernetes, Kafka, FastAPI, REST APIs
- Quality engineering: Selenium, pytest, UAT, regression strategy, CI/CD, telemetry
- Business analysis: requirements, process mapping, acceptance criteria, stakeholder alignment
- Business Analyst Aide, ASU Admission Services
- M.S. Computer Science, Arizona State University, expected January 2027
- Building production-minded Salesforce, cloud, and applied AI systems
- Salesforce Certified Administrator
- Salesforce Certified Platform App Builder
- Salesforce Certified AI Associate
- NASA Space Apps Challenge local winner for AstraNode
- Accenture Best Performer Award
- Published computer-vision research
The detailed project narratives, architecture diagrams, recommendations, and resume are available on my portfolio.


