Aly Khaled
Software Engineer at Proteinea, building scientific software for antibody discovery.
قيمةُ كلِّ امرئٍ ما يُحسِنُه
At Proteinea
At Proteinea, I build the compute platforms, AI infrastructure, and research interfaces that help scientists design and evaluate antibodies at scale.
40+
tools shipped in a dynamic registry
1K+
jobs orchestrated each month
20+
drug discovery projects supported
99.9%
job status accuracy in production analytics
I'm Aly Khaled, a software engineer from Egypt with a background in biomedical engineering. At Proteinea, I build scientific and AI infrastructure for antibody engineering and computational biology.
A core part of my work is a scientific computing platform with a schema-driven registry of 40+ tools. It orchestrates more than 1,000 jobs each month across cloud GPUs and an on-premise Slurm cluster, giving researchers a consistent way to run complex computational workflows.
I also helped build an antibody design platform used across 20+ discovery projects. It brings AI-driven variant generation, interactive structure analysis, and responsive interfaces for datasets with more than one million rows into a single research workflow.
Behind those products, I work on the infrastructure that keeps research moving: containerized GPU execution, job submission and scheduling, analytics dashboards, and monitoring with Grafana and Prometheus. That work reduced recovery time by 40% and made the state of long-running experiments easier to understand.
Proteinea has shaped how I think about software. I enjoy technically deep products where infrastructure, data, AI, and product design have to work together—and where better tools give scientists more time to focus on discovery.
Earlier in my career, I built healthcare systems for more than 100,000 users and machine-learning tooling that reduced model size by 50% and training time by 70%. Those experiences taught me to build for real constraints, but scientific software is where that work now comes together.
- Turn complex scientific data into decisions teams can actually act on.
- Compress expert workflows from days into minutes without losing rigor.
- Build software that is technically serious, operationally reliable, and directly useful.
If you're working on scientific computing, antibody discovery, or AI systems for research teams, we should talk.
My work at Proteinea sits at the intersection of computational biology, AI infrastructure, and product engineering. I'm always interested in conversations with researchers and engineers building serious tools for science. Email is the fastest path.