I am a technical solutions professional with extensive experience translating complex enterprise requirements into scalable architectures that accelerate client time-to-value. I have a proven track record of owning the full project lifecycle from discovery to deployment, including scoping technical solutions, onboarding enterprise clients, and bridging the gap between engineering and business stakeholders across B2B SaaS platforms serving thousands of enterprise users.
My hands-on background includes distributed systems, enterprise identity and access patterns, and agentic AI. I consistently focus on reducing friction, shortening delivery cycles, and building self-service tools that empower non-technical teams to operate independently. I am equally comfortable whiteboarding architecture with engineers and presenting trade-offs to senior business leadership.
Currently, I advise enterprise clients on AI adoption strategies, running technical discovery, scoping integration architectures, and translating large language model capabilities into actionable deployment plans for both technical and business stakeholders. I have designed and built model-agnostic multi-agent orchestration frameworks with role-isolated threads and human-in-the-loop approval logs, demonstrating production-grade agentic architecture with auditability and controlled autonomy.
I have implemented evaluation suites measuring task completion, tool accuracy, and iteration efficiency across agentic workflows, applying trace-based analysis to identify and resolve reliability gaps. Additionally, I developed a retrieval-augmented generation proof-of-concept using FAISS and semantic retrieval to ground LLM outputs in user-specific data, showcasing practical applications of context engineering for enterprise personalization.
Previously, I worked as a Full Stack Engineer for a B2B SaaS analytics platform serving luxury brands, where I owned enterprise identity and access control, led authentication and authorization overhauls, and served as the primary technical contact for client onboarding and solution design. I successfully reduced delivery cycles by designing self-service configuration tooling and rebuilt distributed report delivery pipelines for high uptime and reliability.
My academic background includes a Bachelor of Science in Biochemistry with a minor in Neuroscience from McGill University, where I also held leadership roles and managed significant budgets. This cross-disciplinary foundation supports my credibility in technically complex, multi-stakeholder enterprise environments.
GPA: 3.7/4.0; Major Scholarship Recipient; Vice President, Science Undergraduate Society – managed $300k+ budget and events for 1,000+ attendees; Cross-disciplinary background spanning life sciences, data systems, and software engineering
Advising enterprise clients on AI adoption strategy including technical discovery, scoping integration architectures, and translating LLM capabilities into deployment plans; Designed and built model-agnostic multi-agent orchestration framework with role-isolated threads and human-in-the-loop approval logs; Implemented evaluation suite measuring task completion, tool accuracy, and iteration efficiency; Built RAG proof-of-concept using FAISS and semantic retrieval; Developing vertical SaaS booking platform with client tracking, real-time scheduling, and RBAC-controlled admin workflows.
Owned enterprise identity and access control across multi-tenant platform including RBAC, data partitioning, OAuth/Auth0 integration, and audit logging; Led authentication and authorization overhaul during QlikView to React migration; Served as primary technical contact for enterprise client onboarding and solution design; Reduced delivery cycles by designing self-service configuration tooling; Rebuilt distributed report delivery pipeline for 24/7 uptime; Designed event-driven data ingestion and analytics backend with BigQuery and relational databases; Built observability tooling for monitoring and debugging.
Supported neuroscience and biochemistry research; optimized data analysis workflows; trained cross-functional junior team members.
Jobicy
614 professionals pay to access exclusive and experimental features on Jobicy
Free
USD $0/month
For people just getting started
Plus
USD $8/month
Everything in Free, and: