Enterprise Solutions Architect @ Redis
I design distributed systems that hold up at enterprise scale.
Cloud migrations, low-latency architecture, and applied AI — for enterprise teams running Redis and MongoDB at scale.
About
Background
I'm an engineer who moved from writing production code to sitting across the table from enterprise engineering teams — first at MongoDB, now at Redis — helping them design systems that hold up under real-world scale. My work spans architecture reviews, cloud migrations, and hands-on proofs of concept, with a growing focus on the infrastructure behind AI: retrieval pipelines, context engineering, and cost-efficient agentic systems.
Before moving into solutions architecture and developer advocacy, I spent years as a software engineer at Postman and MongoDB, shipping product experiences and developer tools used by tens of millions of people. That background shapes how I work today: I care about distributed systems that are simple to reason about, and about explaining complex technical tradeoffs clearly — whether that's in a workshop, a design review, or a 1:1 with an engineering team evaluating a migration.
Experience
Work history
Six years across enterprise infrastructure, developer advocacy, and product engineering.
October 2025 — Present
Enterprise Solutions Architect · Redis Inc.
- Architected scalable, low-latency (<1ms), high-throughput solutions on Redis Enterprise Cloud, Kubernetes, and On-Premise.
- Led cloud modernisation design reviews with engineering teams, producing reusable reference architectures for high-availability, active-active deployments across AWS and Google Cloud.
- Led end-to-end cloud migrations to Redis Enterprise from AWS ElastiCache, Google MemoryStore, and Redis OSS, owning technical planning, risk assessment, and cutover execution.
- Reduced LLM token consumption by 35% on average by redesigning retrieval strategies using LangCache, optimizing enterprise AI workloads for cost efficiency through context engineering.
- Designed ultra-fast (<50ms) vector retrieval pipelines combining Redis with embedding models, enabling production-grade agentic AI applications for enterprise customers.
August 2023 — October 2025
Senior Developer Advocate · MongoDB Inc.
- Drove developer adoption of MongoDB's developer data platform across APAC through in-person technical workshops and webinars, directly supporting pipeline generation and deal progression alongside sales teams.
- Led enterprise architecture design reviews with engineering and infrastructure teams, translating technical requirements into optimized solutions across schema design, query performance, and AI-driven workloads.
- Designed cloud-native architectures that enabled customers to modernise their data infrastructure, integrating MongoDB Atlas with AWS, Google Cloud, and Azure.
- Partnered cross-functionally with sales, product, and engineering to surface customer feedback, influence roadmap priorities, and ensure technical alignment with platform capabilities.
January 2023 — August 2023
Software Engineer · Postman Inc.
- Holistically improved core product experience for 20M users by optimizing workspace UX and interaction flows.
- Leveraged analytics to identify user behavior patterns and increase retention through targeted UX improvements.
- Collaborated within a Bitbucket-based DevSecOps workflow, participating in code reviews, branch management, and CI/CD pipeline runs.
- Mentored for Google Summer of Code 2023 on the schema.org project hosted by Postman.
February 2021 — January 2023
Software Engineer 2 · MongoDB Inc.
- Built and optimized components for MongoDB University, improving the learning experience for 2M+ users.
- Automated deployment workflows using Node.js — converted a ~30 minute manual Jenkins task into a 7ms script.
- Implemented CI/CD pipelines through GitHub Actions for efficient deployment and testing.
- Created an open-source JS library enabling developers to perform analytics on offline-first mobile apps using Atlas Device Sync and Realm's React Native SDK.
- Official MongoDB Developer Center author with tutorials on building full-stack applications.
May 2020 — September 2020
Business Analyst Intern · Springworks
- Built full-stack architectures using Node.js and React.js, with efficient, automated task scheduling.
- Analyzed KPIs and created optimized aggregation pipelines for MongoDB.
- Optimized the ETL process for data analysis, resulting in 70% faster query performance and enriched reporting.
May 2019 — June 2019
Software Engineering Intern · Springworks
- Implemented APIs using Node.js, MongoDB, Express.js, and AWS for marketing leads enrichment.
- Integrated order checkout and payments on a web app that manages background verification requests.
Selected Work
Enterprise architecture, cloud migrations, and applied AI
A sample of the architecture, migration, and AI infrastructure work behind the roles above.
Speaking & Community
Workshops, mentorship, and community leadership
How I Work
Principles
Optimize for measurable outcomes
Every design decision should move a real number — a 35% cut in LLM token spend, a 30-minute deploy turned into 7ms, a 70% faster query. If it can't be measured, it can't be improved.
Design for scale and latency from day one
Sub-millisecond Redis architectures and sub-50ms vector retrieval don't happen by accident. Latency budgets and failure modes belong in the first design review, not the postmortem.
De-risk migrations before you execute them
Cloud migrations succeed on planning, not heroics — technical assessment, risk mapping, and a clear cutover plan come before a single system is touched.
Bridge engineering and business
Technical wins only matter if they land — that means translating architecture into terms that account teams, engineering leads, and enterprise buyers all trust.
Teach as you build
Workshops, open-source libraries, developer tutorials, and mentoring aren't separate from the engineering work — they're how good architecture decisions compound across teams.
Contact
Let's talk
Open to conversations about enterprise architecture, cloud migrations, and applied AI infrastructure.