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 motivated Software Engineer, Security Engineering to help build and operate security across Bot Auto's autonomous trucking stack. The proprietary technology that powers our autonomous driving system is our core intellectual property, and protecting it - along with the safety-relevant systems behind our fleet - is mission critical. In this role, you will work with experienced engineers across onboard (in-vehicle) security as well as infrastructure and platform security. You will contribute to how Bot Auto adopts AI responsibly by helping assess risks in large language models and agentic systems and implementing practical protections. This is a hands-on role with opportunities to learn across the full stack, from the vehicle to the cloud, while building strong foundations in security engineering. Key Responsibilities Implement and maintain security controls for onboard (in-vehicle) systems, including secure boot, code signing, secrets and key management, secure over-the-air (OTA) updates, and system hardening. Support security across infrastructure and platforms, including Kubernetes, public cloud (AWS), on-prem data centers, CI/CD pipelines, and internal developer platforms. Help evaluate and implement protections for AI systems, including defenses against prompt injection, data exfiltration, model and supply-chain risks, and unsafe agent behavior. Build and maintain identity and access management, secrets management, and least-privilege authorization for services, devices, and fleet systems. Participate in threat modeling, security design reviews, and risk assessments, and partner with engineering teams to address identified issues. Help operate vulnerability management, dependency and supply-chain scanning, and secure software development lifecycle (SSDLC) tooling and processes. Contribute to security detection, logging, monitoring, and incident response across onboard and infrastructure environments. Improve security through automation, documentation, testing, and close collaboration with software, platform, and autonomy engineering teams. Required Qualifications Bachelor's degree in Computer Science, Engineering, Cybersecurity, or a related field, or equivalent practical experience 0-2 years of software engineering, security engineering, or related experience; relevant internships, research, projects, or open-source contributions are welcome Programming experience in one or more languages such as Python, Go, Rust, C/C++, or JavaScript/TypeScript Foundational understanding of authentication and authorization, networking, operating systems, and common software security vulnerabilities Familiarity with Linux and cloud or distributed systems, with an interest in learning how to secure production environments Preferred Qualifications Internship, coursework, project, or hands-on experience in cybersecurity, embedded systems, automotive, IoT, or edge computing Familiarity with containers, Kubernetes, AWS, infrastructure as code (Terraform, Pulumi), or CI/CD systems Interest in or exposure to AI/LLM security topics such as prompt injection, model supply chain, agent sandboxing, or AI guardrails Familiarity with IAM, secrets management, PKI, or zero-trust concepts Experience with security tooling such as SAST/DAST, dependency scanning, SBOMs, SIEM, or vulnerability scanners through work, coursework, or personal projects Awareness of security standards and frameworks such as ISO/SAE 21434, NIST, OWASP, or SOC 2 Exposure to threat modeling, incident response, capture-the-flag exercises, security research, or responsible vulnerability disclosure

Requirements

Must-haves

Company Introduction
Implement and maintain security controls for onboard (in-vehicle) systems, including secure boot, code signing, secrets and key management, secure over-the-air (OTA) updates, and system hardening.
Support security across infrastructure and platforms, including Kubernetes, public cloud (AWS), on-prem data centers, CI/CD pipelines, and internal developer platforms.
Help evaluate and implement protections for AI systems, including defenses against prompt injection, data exfiltration, model and supply-chain risks, and unsafe agent behavior.
Build and maintain identity and access management, secrets management, and least-privilege authorization for services, devices, and fleet systems.
Participate in threat modeling, security design reviews, and risk assessments, and partner with engineering teams to address identified issues.
Help operate vulnerability management, dependency and supply-chain scanning, and secure software development lifecycle (SSDLC) tooling and processes.
Contribute to security detection, logging, monitoring, and incident response across onboard and infrastructure environments.
Improve security through automation, documentation, testing, and close collaboration with software, platform, and autonomy engineering teams.
Bachelor's degree in Computer Science, Engineering, Cybersecurity, or a related field, or equivalent practical experience
0-2 years of software engineering, security engineering, or related experience; relevant internships, research, projects, or open-source contributions are welcome
Programming experience in one or more languages such as Python, Go, Rust, C/C++, or JavaScript/TypeScript
Foundational understanding of authentication and authorization, networking, operating systems, and common software security vulnerabilities
Familiarity with Linux and cloud or distributed systems, with an interest in learning how to secure production environments

Nice-to-haves

Internship, coursework, project, or hands-on experience in cybersecurity, embedded systems, automotive, IoT, or edge computing
Familiarity with containers, Kubernetes, AWS, infrastructure as code (Terraform, Pulumi), or CI/CD systems
Interest in or exposure to AI/LLM security topics such as prompt injection, model supply chain, agent sandboxing, or AI guardrails
Familiarity with IAM, secrets management, PKI, or zero-trust concepts
Experience with security tooling such as SAST/DAST, dependency scanning, SBOMs, SIEM, or vulnerability scanners through work, coursework, or personal projects
Awareness of security standards and frameworks such as ISO/SAE 21434, NIST, OWASP, or SOC 2
Exposure to threat modeling, incident response, capture-the-flag exercises, security research, or responsible vulnerability disclosure

Application prep

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Keywords to mirror

aikubernetesawsci/cdpythongorustjavascripttypescriptllm

Platform: greenhouse
Effort: quick

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Vision