Bot Auto
Technology
SeniorSoftwareEngineer,WorkflowPlatforms
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer, Workflow Platforms at Bot Auto. Skills: Workflow orchestration, Kubernetes, Platform engineering, DevOps. Architect workflow orchestration platforms. Deploy workflow orchestration platforms”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience, 5+ years of hands-on experience in platform engineering, infrastructure, DevOps, or SRE roles, Significant experience with workflow orchestration platforms such as Argo Workflows, Airflow, or comparable systems, Software development skills in one or more languages: Python, Go, Java, or JavaScript/TypeScript, Solid understanding of Kubernetes and distributed systems
Nice to Have
Expert-level experience operating Argo Workflows, Airflow, and/or other engines, Experience orchestrating ML training, simulation, or large-scale data and batch workloads, including GPU scheduling, In-depth Kubernetes experience (EKS, GKE, AKS, RKE2/Rancher) and cross-cluster orchestration, IaC tools proficiency, including Terraform, Pulumi, OpenTofu, or Ansible, Experience with data streaming and event platforms, including NATS JetStream, Kafka, Pulsar, or RabbitMQ, Familiarity with observability stacks: Prometheus, Grafana, Loki, OpenTelemetry, or comparable, Demonstrated ability to optimize workload cost and performance without compromising reliability
What You'll Do.
Architect workflow orchestration platforms
Deploy workflow orchestration platforms
Operate workflow orchestration platforms
Build internal platforms
Build self-service tooling
Operate workflow platforms at scale on Kubernetes
Handle GPU and heterogeneous resources
Handle cross-cluster orchestration
Ensure reliability of workloads
Ensure performance of workloads
Ensure cost efficiency of workloads
Partner with ML teams
Partner with simulation teams
Partner with data teams
Partner with infrastructure teams
Understand workload requirements
Deliver fit-for-purpose pipelines
Integrate workflow platforms with storage
Integrate workflow platforms with data streaming systems
Integrate workflow platforms with event systems
Integrate workflow platforms with artifact registries
Integrate workflow platforms with model registries
Integrate workflow platforms with CI/CD tooling
Establish best practices
Establish documentation for workflow authoring
Mentor engineers across the company
Handle user-impacting issues promptly
Mitigate issues in the short term
Follow up with durable long-term solutions
How You'll Work.
Team & Collaboration
Partner with ML teams; Partner with simulation teams; Partner with data teams; Partner with infrastructure teams
Communication Scope
Clear communication
Full Job Description
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 highly skilled and motivated Senior Software Engineer, Workflow Platforms to architect, build, and operate the workflow orchestration platforms that power Bot Auto's engineering and autonomy workloads. From simulation and machine learning training to data pipelines and CI/CD, our teams depend on reliable, scalable workflow systems to move fast. In this role, you will own one or a hybrid of orchestration platforms (such as Argo Workflows and Airflow), operate them at scale, and develop the internal platforms and abstractions built on top of them that make running complex workloads simple, observable, and cost-efficient. Key Responsibilities Architect, deploy, and operate workflow orchestration platforms (e.g., Argo Workflows, Airflow, or a hybrid) supporting simulation, machine learning and model training, data pipelines, CI/CD, and other general-purpose workloads. Build internal platforms, abstractions, SDKs, and self-service tooling on top of orchestration engines to make authoring, running, and monitoring workflows simple and reliable for engineers. Operate workflow platforms at scale on Kubernetes across cloud (AWS) and on-prem data center environments, handling scheduling, autoscaling, GPU and heterogeneous resources, and cross-cluster orchestration. Ensure reliability, performance, and cost efficiency of workloads through observability, queuing and prioritization, retries, and resource optimization. Partner with ML, simulation, data, and infrastructure teams to underst
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