Staff Software Engineer (AI)

Location: Sunnyvale, California, USA; hybrid working model with in-person collaboration and remote work.

Salary: $276,100–$293,750 annually, plus equity.

Company

hirify.global builds an AI platform for autonomous driving, developing mapless, hardware-agnostic driving intelligence for global OEM partners and vehicles.

What you will do

• Own the architecture and operation of cloud services supporting the AI model lifecycle, including data workflows, training, experiment scheduling, evaluation, and on-road testing.
• Design reliable, observable, secure, and scalable platform services with defined availability, latency, and performance targets.
• Build identity, authentication, authorization, auditability, microservices, micro-frontends, CI/CD, progressive delivery, rollback, alerting, and self-healing infrastructure.
• Lead significant services and multi-quarter initiatives from problem definition and design through deployment and production operation.
• Set reusable technical patterns through design reviews and collaboration across data pipelines, experiment scheduling, distributed compute, Product, Research, Design, and Operations.
• Mentor engineers and remain hands-on across backend services, web applications, and cloud infrastructure.

Requirements

• 7+ years designing and building large-scale distributed systems, cloud platforms, or developer platforms, including experience at senior or staff level.
• Experience designing and operating scalable microservice architectures on a major cloud provider, including API design, data modeling, asynchronous workflows, and distributed-systems fundamentals.
• Hands-on experience implementing authentication and authorization, such as OAuth2/OIDC and RBAC, using sound security practices.
• Experience driving reliability improvements, defining SLAs/SLOs, and building observable, self-healing, highly available systems.
• Experience with CI/CD, containerization, orchestration such as Kubernetes, infrastructure as code, and safe release and rollback strategies.
• Ability to write and review production-quality code in Python or TypeScript, with understanding of modern web architectures including React and micro-frontends.
• Track record of taking significant services from design through deployment and production operation.
• Strong communication and cross-functional collaboration skills, including mentoring through design discussions, code reviews, and pairing.

Nice to have

• Experience building internal developer platforms, workflow systems, or tools for ML researchers and engineers.
• Familiarity with MLOps, including training, evaluation, experiment tracking, and artifact management.
• Experience with data pipelines, distributed job orchestration, event-driven architectures, or large-scale compute such as Spark, Ray, Airflow, or MLflow.
• Experience with service mesh, API gateways, feature flags, or progressive-delivery tooling.
• Knowledge of privacy, compliance, and secure handling of sensitive or large-scale data.
• Experience in autonomous systems, robotics, simulation, or another safety-critical domain.

Culture & Benefits

• Hybrid work with dedicated offices, core hours, and opportunities to work hands-on in vehicle workshops and labs.
• Meaningful equity and market-benchmarked salaries.
• Relocation support and visa sponsorship where applicable.
• Learning and development budgets for training, conferences, and growth.
• Health, dental, parental leave, retirement or pension benefits where applicable, therapy access, wellbeing partnerships, and team socials.
• Inclusive, respectful culture with substantial ownership in shaping evolving ways of working.

Hiring process

• Recruiter screen followed by a hiring-manager meeting.
• Deep-dive technical interviews covering programming, system design, and domain-specific topics; four hours total.
• Final interview focused on mission and values alignment.