Software Engineer with 12+ years of experience building high-scale, cloud-native backend services and distributed systems, specializing in Go-based microservices, LLM-orchestration loops, and autonomous multi-agent systems. Proven track record designing agentic AI platforms that reason over multi-year proprietary datasets, execute unsupervised analytical investigations, and surface fraud, billing errors, and hidden risk with strict multi-tenant isolation. Deep expertise in Go, Python, and JavaScript across the stack, with production experience in LLM tool-calling, supervisor-coordinated agents, real-time data pipelines, and big-data environments. Recognized for shipping greenfield production AI platforms at scale, applying Agile principles, and delivering financial intelligence that reports each finding as a specific asset, a dollar amount, and a recommended action
Benjamin Cheng
@benjamincheng2
Senior Software Engineer
United StatesExperience
Work history, roles, and key accomplishments
Built a production multi-agent system that reasons over multi-year enterprise financial and operational data to autonomously surface fraud, ghost assets, billing errors, and hidden risk, reporting each finding as a specific asset, a dollar amount, and a recommended action. The platform runs unsupervised overnight investigations and answers in
plain language.
Designed an agentic analytics layer that autonomously investigated enterprise back-office controls, detecting billing
discrepancies, hidden risk, and anomalous asset records across multi-tenant SaaS environments. The system combined
LLM-driven reasoning with real-time data pipelines to deliver plain-language findings with dollar-quantified impact and
recommended actions.
Contributed to an intelligent data platform that applied analytical reasoning and anomaly detection over multi-year
operational datasets, surfacing hidden risk and data-quality issues in near real time. The system emphasized reliable
backend services, strict data isolation, and plain-language reporting for business stakeholders.
Built enterprise analytics services that detected anomalies, billing discrepancies, and hidden risk across financial backoffice systems, laying groundwork for autonomous investigation workflows. The platform combined distributed data
processing with rule-based and statistical reasoning to deliver actionable findings to enterprise customers.
Education
Degrees, certifications, and relevant coursework
University of Illinois Urbana-Champaign
Bachelor of Science, Computer Science
2008 - 2011
Bachelor of Science in Computer Science from the University of Illinois Urbana-Champaign, completed in 2011.
Availability
Location
United StatesAuthorized to work in
Salary expectations
Social media
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