Founding Engineer — Orchestration & Distributed ML

About the Company
Neura Augma (Neau AI) is an autonomous intelligence research and product company focused on making autonomous intelligence as trusted as the experts it serves in healthcare. Our product, HALE is an execution layer for healthcare AI, designed to solve one of the field’s foundational challenges: the lack of a reliable health data foundation for practical, scalable, and autonomous AI.

Role Overview
You will be the founding engineer responsible for architecting and building orchestration, automation, and runtime systems that form the backbone of our offering. This role requires designing a globally distributed processing system that operates reliably at scale while preserving privacy, security, and performance across heterogeneous healthcare environments. It blends distributed systems engineering with Harness‑style platform work across ML pipelines, deployment automation, secure runtimes, and multi‑environment coordination. This is an equity-forward founder-type role with meaningful ownership.

Key Responsibilities

• Build infrastructure for federated learning execution
• Build orchestration systems for globally distributed workloads, runtime coordination, and large-scale processing
• Develop secure execution runtimes for AI and data workflows
• Design APIs and service interfaces for internal and external developers
• Automate deployments and environment provisioning workflows
• Own harness style engineering across pipelines, deployment, runtime automation, and multi‑environment coordination
• Implement strong identity, access, isolation for healthcare data and distributed execution environments.

Ideal Background

• Deep expertise in distributed computing, orchestration, and scalable processing systems
• Strong programming experience in Rust and Python for systems, orchestration, automation, and ML infrastructure
• Hands-on experience building cloud infrastructure on AWS and Azure, including deployment, networking, identity, and secure infrastructure patterns
• Strong runtime and containerization skills
• Strong understanding of networking and identity
• Comfort with event driven architectures (Kafka, Kinesis, or similar)
• Interest in orchestrating hybrid classical–quantum algorithms
• Familiarity with EHR standards such as OMOP/FHIR is a plus
• Founder mindset: hands-on, pragmatic, comfortable owning large surface areas

What Success Looks Like
Success means delivering a secure, privacy‑preserving, globally distributed system that reliably runs federated AI workloads across heterogeneous environments — with a unified control plane, automated data‑plane workflows, and consistent, isolated, fast iteration across all sites.