Senior Security Software Engineer, Advanced Security (AI)

Location: Hybrid in Austin, Texas or Warren, Michigan; expected to report to a specific location at least 3 times per week or at another frequency set by the manager.

Company

hirify.global develops automotive products and security capabilities aligned with its vision of Zero Crashes, Zero Emissions, and Zero Congestion.

What you will do

• Design, build, and operate production Python cloud services with containerized workloads, event-driven processing, data storage, and infrastructure as code.
• Integrate security findings and context from security tools, source control, and cloud APIs; build AI agents that triage findings, gather evidence, and propose fixes.
• Build and harden sandboxed environments for authorized AI-enabled security testing using defense in depth, isolation, least-privilege identities, network egress controls, and secrets management.
• Protect sensitive security data and systems from untrusted code, tool output, model responses, prompt injection, and unsafe logging.
• Evaluate model accuracy, cost, and latency; identify regressions and use evidence to guide technical trade-offs.
• Partner with application security, penetration testing, and cloud security engineers, communicate risks, review code, and mentor other engineers.

Requirements

• Bachelor’s degree in Computer Science, Cybersecurity, Engineering, or a related field, or equivalent practical experience.
• 5+ years of experience in software engineering, cloud engineering, or security engineering.
• Strong experience writing production Python.
• Experience with infrastructure as code such as Terraform and CI/CD on a major cloud platform.
• Working knowledge of application security, common vulnerability classes, security scanners, and their false positives.
• Experience building secure systems using least privilege, secrets management, isolation, and safe handling of untrusted input.
• Ability to own work across teams, make decisions with limited information, and explain technical risk to non-specialists.
• Experience using agentic large language model tools and solutions.

Nice to have

• Experience building applications with large language models and agent frameworks, including tool use and output evaluation.
• Experience with containers and Kubernetes.
• Experience with sandboxing, isolation, or securing systems that execute untrusted code.
• Experience with static or program analysis, including Semgrep or CodeQL rules.
• Experience in vulnerability research, penetration testing, or exploit development.
• Familiarity with AI security risks and controls, including the OWASP Top 10 for LLM Applications.
• Public examples of shipped work, such as open-source contributions, published tools, or technical write-ups.

Culture & Benefits

• Hybrid work with regular attendance at the assigned location.
• Relocation benefits are available for candidates who qualify under company policy.
• Employment benefits support well-being at work and at home.
• GM promotes inclusion, belonging, and a non-discriminatory workplace.
• Immigration-related sponsorship is not provided, including H-1B, OPT, STEM OPT, CPT, TN, J-1, or other company-supported work authorization.

Hiring process

• Applicants may be required to complete role-related assessments and/or pre-employment screening where applicable.
• Applications must be submitted for roles matching the candidate’s skills and capabilities.