Senior Full Stack Engineer

Ohalo•Aptos, CA

13h

About The Position

Ohalo is seeking an experienced Senior Fullstack Engineer to build and evolve internal platforms that power our breeding, automation, and machine-learning workflows. This role spans backend services, data systems, web applications, and mobile tools, enabling scientists, engineers, and operators to interact with complex systems in reliable, intuitive ways. You’ll focus on internal tooling, system integration, and platform reliability—building the connective tissue between robotics, ML pipelines, and human workflows.

Requirements

Bachelor’s degree in a technical field (Computer Science, Engineering, or similar).
5+ years of experience as a Fullstack, Platform, Backend, or Infrastructure-oriented Engineer.
Strong backend experience with Python and frameworks such as FastAPI.
Proficiency with frontend development (e.g., React) and mobile development using React Native.
Hands-on experience operating cloud infrastructure on GCP (preferred) or AWS.
Experience with infrastructure-as-code, CI/CD pipelines, and production deployments.
Experience designing and operating service-oriented and event-driven systems.
Familiarity with messaging and streaming platforms (Pub/Sub, Kafka).
Strong systems thinking, with the ability to reason across product, platform, data, and infrastructure layers.
Comfortable working independently in a cross-functional, distributed environment.
Clear communicator who can collaborate effectively with science, ML, and automation teams.

Responsibilities

Design, build, and own internal platforms and infrastructure used by science, ML, and automation teams.
Develop and maintain backend services and APIs using Python (FastAPI) that support web, mobile, and ML-driven workflows.
Build and maintain fullstack internal applications, including: Web frontends (e.g., React) Mobile applications using React Native for operational and field workflows
Design and operate cloud infrastructure on GCP, including networking, compute, storage, and IAM.
Manage infrastructure-as-code (e.g., Terraform, Pulumi) and deployment pipelines.
Build and evolve scalable data platforms using BigQuery, Python, and Spark.
Implement and maintain service-oriented and event-driven architectures using Pub/Sub, Kafka, and related tooling.
Partner with ML engineers to support model deployment, orchestration, and production integration.
Establish and maintain observability, reliability, and security across services and infrastructure (logging, metrics, alerting).
Improve developer experience through better abstractions, tooling, CI/CD, and documentation.
Proactively identify and address scalability, performance, and operational risks across the platform.