I
Staff Architect, Data & AI Infra
·Israel
HybridFull-timeDevOps & SREBiotechnology
An AI-driven platform company in biotechnology is seeking a Staff Architect to own and evolve the technical roadmap for data and AI platforms, ensuring scalable and reliable architecture. The role involves building MLOps systems, managing GPU and data infrastructure, improving developer experience, and leading a small team.
Responsibilities
- Own and evolve the technical roadmap for data and AI platforms, ensuring scalable architecture for a multi-cloud future.
- Design and build end-to-end MLOps systems for experimentation, training, reproducibility, and deployment, managing BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
- Define strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
- Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates.
- Act as a player-coach, mentoring engineers and managing a small team of ICs, fostering technical excellence.
- Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, improving observability, incident readiness, and support processes.
Requirements
- 8+ years of industry experience in infrastructure, platform, data, or ML engineering, with deep background in designing production infrastructure for data-intensive or AI/ML systems.
- Hands-on expertise building and operating MLOps systems and managing GPU infrastructure, including scheduling, resource management, and utilization.
- Proficient in managing data infrastructure technologies (e.g., BigQuery, data warehouses, object storage, orchestration systems like Dagster or Airflow) and operating within Kubernetes/containerized environments.
- Demonstrated ability as a player-coach, including people-management experience or leading small engineering teams, with a focus on mentoring senior engineers.
- Strong communication skills with the ability to partner effectively across diverse groups including Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership.
Nice to have
- Proven ability to build internal developer platforms, 'golden paths', and self-service infrastructure to reduce operational friction.
- Experience leading engineering teams through transition toward AI-first development processes.
- Strong background operating within regulated environments (SOC2, HIPAA, GDPR) and applying infrastructure best practices to biotech, life sciences, or bioinformatics.