Teams at Bot Auto

Architect, build, deploy, and operate production-grade AI agentic systems and workflows. Responsibilities include backend and full-stack development, agent orchestration, workflow state, retrieval, memory, approvals, failure recovery, data architecture, enterprise integrations, cloud infrastructure, observability, security, and scaling. The role establishes reusable engineering patterns and partners with users to deliver reliable AI products, while addressing production issues involving model behavior, permissions, latency, cost, and consistency.

Design, deploy, and operate large-scale workflow orchestration platforms (Argo/Airflow/hybrid) for simulation, ML training, data pipelines and CI/CD. Build SDKs, abstractions, and self-service tooling; ensure reliability, observability, cost-efficiency, GPU and cross-cluster scheduling on Kubernetes across cloud and on-prem; integrate with storage, streaming, registries, and CI/CD; document best practices and mentor engineers.

Develop and research deep learning and vision algorithms for autonomous driving (detection, tracking, prediction, planning, SLAM). Lead end-to-end ML projects from data analysis through model evaluation, and collaborate across product, simulation, and algorithm teams to extend ML technologies into system components.