Software Engineer (AI Backend)

Location: Hybrid, with positions in New York City, Silicon Valley, Copenhagen, London, or Zurich

Salary: $200,000–$400,000 per year, plus equity

Company

hirify.global is an applied AI company building foundational hardware and software for the semiconductor industry, AI infrastructure, and systems engineering.

What you will do

• Build runtime and orchestration services for AI agent execution, session lifecycles, long-running workflows, and distributed workloads.
• Design reliable backend services, data models, and internal APIs for product, AI, and execution systems.
• Develop persistence, retries, queues, leases, cancellation, recovery, and other distributed-state mechanisms.
• Manage containerized workloads in Kubernetes-backed environments, including lifecycle, isolation, autoscaling, and resource allocation.
• Improve reliability and observability through metrics, tracing, debugging tools, and clearly defined failure modes.
• Turn AI prototypes into durable production systems and facilitate technical design discussions across engineering functions.

Requirements

• 4+ years of software engineering experience in backend systems, distributed systems, developer platforms, production infrastructure, or a related field.
• Strong backend fundamentals, including API design, data modeling, concurrency, debugging, testing, reliability, and maintainability.
• Experience reasoning about distributed state and failure modes, including retries, queues, leases, scheduling, idempotency, and long-running workflows.
• Practical experience with containers and Kubernetes-backed systems, including workload lifecycle, networking, resource limits, and production debugging.
• Experience with production data systems such as Postgres, Redis or Valkey, and object storage.
• Experience building orchestration systems, workflow engines, job schedulers, sandboxes, developer platforms, or distributed execution systems.

Nice to have

• Experience building systems for AI agents, model orchestration, code execution, or LLM-powered products.
• Deep Kubernetes knowledge covering controllers, scheduling, networking, storage, autoscaling, or resource isolation.
• Experience with secure or sandboxed code execution.
• Background in reliability engineering, infrastructure software, or developer platforms at meaningful scale.
• Experience in high-growth environments with evolving systems and ownership boundaries.

Culture & Benefits

• Full-time employment with a hybrid work arrangement.
• Collaboration across engineering, product, AI, research, and platform teams.
• Competitive compensation based on role, skills, experience, and location.
• Equity offered as part of the compensation package.
• Inclusive workplace with equal employment and accessibility commitments.