Technical Lead · Senior Software Engineer · Founding Engineer
Build from Zero. Scale to Millions.
I'm Pablo Magnaghi. I build production systems at two extremes: Amazon-scale distributed systems (1.2M events per minute, caching designed for 300K+ TPS) and zero-to-one AI platforms as a founding engineer.
Buenos Aires, Argentina · working in US time zones
- years building production systems
- 12+
- events per minute after a 6x scale-up
- 1.2M
- TPS: the peak a caching layer I built was designed for
- 300K+
- lower cost per AI video reprocessing run
- 30x
Selected work
Case studies
Selected engineering work and measurable results. Project descriptions are intentionally high-level to respect employer confidentiality.
3,500+production videos searchable by meaning
An AI video platform, from an empty AWS account to production
Semantic search across thousands of TV-length videos: upload, transcode, enrich with AI models and index, built and run end to end as the founding engineer.
Read the case study →6xthroughput: 200K → 1.2M events per minute
Scaling a time-critical event pipeline 6x
From 200K to 1.2M events per minute on a queue-based pipeline where a late event counts as a failed one.
Read the case study →300K+TPS peak traffic the layer was designed for
A distributed caching layer designed for 300K+ TPS
A self-service caching layer in front of a critical, read-heavy service: same API for clients, adopted team by team, correct under expiry storms and upstream failures.
Read the case study →About
Two extremes: make it exist, make it scale
I'm a software engineer with 12+ years of experience. Since July 2026 I've worked as an independent consultant, helping early-stage startups turn a working MVP into a foundation that scales. Before that I was the founding engineer of an AI video platform at Social Dept, which I built from an empty AWS account to production. Before that I spent four years across two periods at Amazon Ring, scaling event pipelines and building distributed caching for device data.
I like the two ends of the spectrum: making something exist, and making it hold up at scale. I care about honest trade-offs, idempotent systems, measurable results and cost as a design input.
I work daily with AI-assisted engineering, and this site was built that way: Claude agents per area, small tasks, and a human approving every change.
The same workflow built an interactive system-design reference, a side project with 22 problems, each walked through step by step with its trade-offs.
Skills
- Languages
- AI
- Cloud & Data
Experience
Independent Consultant · Technical Lead (full-time engagements)
Jul 2026 – Present
Stabilized a live hospitality platform in production, cutting errors from ~10,500 to ~330 a week, and built its v2 platform on AWS with an AI-agent harness: ~350 merged pull requests and 2,000+ tests.
Social Dept · Founding Engineer
Aug 2025 – Jul 2026
Owned backend, cloud infrastructure and AI systems end to end: an AI video platform with semantic search across 3,500+ videos.
Amazon Ring · Senior Software Engineer
Jul 2020 – Dec 2021 · Feb 2023 – Jul 2025
Scaled an event pipeline 6x to 1.2M events per minute and built a caching layer designed for 300K+ TPS.
mmhmm · Senior Software Engineer
Dec 2021 – Sep 2022
Introduced reusable architectural patterns across backend services and raised test coverage to 70%.
Fetcher · Software Engineer → Senior Software Engineer
Oct 2018 – Jul 2020
Led the migration from a PHP monolith to Java and Spring Boot, built RabbitMQ pipelines across six ATS integrations, and mentored six engineers.
Earlier · Technical Lead at Solstice · Mobile and backend roles
2014 – 2018
Led a five-engineer team for Rockwell Automation; mobile and backend work before that.
Education
- University of Buenos Aires (FIUBA)
Machine Learning and Big Data (GPA 10/10) · 2018 - University of Buenos Aires (FIUBA)
Engineering Degree in Software Engineering · 2007 – 2014
Working together
How I can help
Full-time roles
Senior, Staff or Founding Engineer roles at US startups, remote from Buenos Aires.
Get in touch →AWS architecture review
An assessment of an event-driven or serverless AWS system covering reliability, scalability and cost, delivered as a written report with prioritized improvements.
Get in touch →AI search pipelines
Semantic search over video, audio or documents: architecture, implementation, retrieval evaluation and production deployment.
Get in touch →Contact
Let's talk
Hiring for a Senior, Staff or Founding Engineer role, or need a hand with AWS or AI search? Send a message or email [email protected].
Email me