Bot Auto
Software Engineer, Core Platforms
Requirements
Candidates must have a bachelor's degree in a relevant field and 0-2 years of experience in software or platform engineering. Proficiency in at least one programming language such as Python or Go, along with knowledge of Linux and containerization, is required.
Responsibilities
The Software Engineer will contribute to the development and operation of Kubernetes-based platforms, including automation, infrastructure-as-code, and internal tooling. They will also support workflow platforms, API gateways, and observability systems while participating in on-call rotations and incident response.
About the role
Company Introduction At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality. We are seeking a curious and motivated Software Engineer, Core Platforms to help build and run the internal platforms our engineering teams rely on every day. Working alongside senior platform engineers, you will develop platform services, automation, and tooling that make our engineers faster, our systems more reliable, and our infrastructure more cost-efficient. This is a hands-on role built for growth: you will ship production code early, get regular mentorship and code review, and build deep experience in Kubernetes, infrastructure-as-code, and distributed systems while supporting groundbreaking work in autonomous transportation. Key Responsibilities Contribute to the development and operation of our Kubernetes-based platforms, including features for scheduling, autoscaling, and internal platform tooling. Write and maintain infrastructure-as-code (e.g., Terraform, Ansible) for on-prem, cloud, and Kubernetes environments, following team standards and reviews. Help build and support workflow platforms that run data pipelines, simulation jobs, ML pipelines, and CI/CD. Assist in deploying and operating self-hosted LLMs and agentic workflows used for internal automation. Support the operation of API gateways and messaging/streaming systems (including MQTT), handling configuration, upgrades, and troubleshooting. Build dashboards, alerts, and logging integrations that improve visibility into platform health. Help track infrastructure costs and implement optimizations identified with senior engineers. Participate in on-call rotations, incident response, and post-incident reviews, with support from experienced teammates. Write clear documentation and runbooks, and help internal users adopt platform services. Required Qualifications Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience 0–2 years of experience in software engineering, platform engineering, DevOps, or SRE (internships, co-ops, and substantial personal or open-source projects count) Solid programming skills in at least one of: Python, Go, Java, JavaScript/TypeScript Working knowledge of Linux, networking fundamentals, Git, and containers (Docker) Eagerness to learn, take feedback, and own tasks from start to finish Preferred Qualifications Hands-on exposure to Kubernetes (EKS, GKE, AKS, RKE2/Rancher, or a local setup like kind/minikube) Experience with AWS, GCP, or Azure, from coursework, projects, or work Familiarity with an IaC tool such as Terraform, Pulumi, OpenTofu, or Ansible Exposure to workflow orchestration tools such as Argo Workflows or Airflow Interest or project experience in running LLMs or building agent-based automation Familiarity with messaging/streaming systems (NATS JetStream, Kafka, Pulsar, RabbitMQ) or API gateways (Kong, APISIX) Experience using Prometheus, Grafana, Loki, OpenTelemetry, or similar observability tools Interest in cost-aware engineering and infrastructure efficiency