Staff Software Engineer (AI Platform)

Location: Remote, United States

Company

hirify.global is building shared AI Core Platform infrastructure for applications and AI agents.

What you will do

• Build and operate shared infrastructure for secure and reliable access to foundation models.
• Develop model gateways, cloud AI services, provider integrations, routing, fallback, usage controls, observability, reliability, and model governance capabilities.
• Identify and develop scalable, performant solutions and shape product strategy and execution across disciplines.
• Establish code architecture and quality standards for production platform systems.
• Mentor and coach engineers and uphold engineering processes that support high-quality delivery.
• Build reusable, self-service platform capabilities in collaboration with engineering, product, security, infrastructure, and AI application teams.

Requirements

• BS/BTech or higher in Computer Science, Engineering, or a related field.
• 8+ years of production-level engineering experience building highly scalable systems.
• 4+ years acting as a trusted technical decision-maker in a team setting and solving for short-term and long-term business value.
• 4+ years working with SQL or other database querying languages on large multi-table datasets.
• Experience architecting, developing, and deploying large-scale distributed systems.
• Experience with cloud technologies such as AWS, Azure, or GCP.
• Experience building continuous integration and continuous development (CI/CD) pipelines.
• Strong familiarity with server-side web technologies such as Java, Python, Scala, C#, C++, or Go.

Nice to have

• Experience building or operating production platform infrastructure, distributed systems, developer platforms, or other high-availability shared services.
• Experience with LLM infrastructure, model gateways, foundation model APIs, or managed AI platforms such as AWS Bedrock, Azure OpenAI, or Google Vertex AI.
• Strong cloud infrastructure experience, preferably AWS, including Kubernetes, containers, and infrastructure as code.
• Experience designing observability and operational practices, including metrics, distributed tracing, logging, alerting, SLOs, dashboards, and failure handling.
• Experience designing APIs and self-service platform capabilities for other engineering teams.
• Experience with identity, access control, secrets management, security, and governance for shared infrastructure.
• Experience with cost management, usage attribution, quotas, budgets, or capacity management for shared platforms.
• Experience operating systems that handle sensitive or regulated data.
• Ability to evaluate architectural tradeoffs across reliability, performance, security, cost, scalability, and developer experience.

Culture & Benefits

• Remote workplace in the United States.
• Collaborative work with engineering, product, security, infrastructure, and AI application teams.
• Focus on secure, maintainable, observable, resilient, and operationally ready systems.