Tomás Fornara
Artificial Intelligence Engineer at Spyderbat
Berlin, Uruguay
Summary
👤
Senior🎓
Top SchoolTomás Fornara is an Artificial Intelligence Engineer based in Berlin with over a decade of hands-on experience building production backend systems that operate at real scale. He combines a strong Java and distributed-systems background—having developed high-throughput hotel and pricing platforms handling billions of records—with modern AI practice, integrating and fine-tuning LLMs, building model-serving pipelines, and monitoring models in production. His career spans startups and enterprise teams (Despegar, QOMPLX, HubSpot) where he shipped data-heavy, low-latency services and led cross-functional engineering efforts. At Spyderbat he bridges applied AI and backend reliability, focusing on end-to-end LLM workflows and multi-provider integrations. Notably, he has deep operational experience with Kafka, Hadoop/Hive, Elasticsearch, and cloud deployments, so his ML work is grounded in proven large-scale engineering. He brings a pragmatic mix of systems thinking, performance tuning, and product-focused delivery that keeps research-driven AI work robust in production.
11 years of coding experience
20 years of employment as a software developer
Information Systems, Information Technology, Information Systems, Information Technology at University of Buenos Aires
English, Spanish, German
Stackoverflow
1,308reputation
202kreached
23answers
0questions
base64
top-5%
kubernetes
top-5%
Github Skills (43)
domain-name10
scraper10
authentication10
linkedin-api10
security10
tld10
discovery10
spring-boot10
hound10
creative-commons10
oauth10
kubernetes9
java9
spring9
spring-security9
Programming languages (3)
Github contributions (5)
TeamHG-Memex/hh-joogle
Jul 2015 - Mar 2016
Contributions:146 pushes, 37 branches in 8 months
TeamHG-Memex/sitehound-frontend
Mar 2017 - Nov 2017
Site Hound (previously THH) is a Domain Discovery Tool
Contributions:1 release, 225 commits, 26 PRs in 8 months
domain-discoveryhounddomain-namesecuritydiscovery
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