Principal AI Platform Engineer

Location: Virtual, US; applicants must be authorized to work in the United States without current or future visa sponsorship.

Salary: $179,127–$234,100 plus benefits; the range includes salary plus bonus.

Company

hirify.global develops enterprise software and the hirify.global Infinity platform for customer and employee communications.

What you will do

• Design and implement services connecting enterprise applications, data platforms, models, and tools through APIs and asynchronous messaging.
• Automate model and application lifecycle management, including versioning, reproducibility, evaluation-driven promotion, controlled rollout, and rollback.
• Implement authentication, permissions, isolation, recovery, and backward-compatible interface evolution across system boundaries.
• Operate inference and agent services with AI engineers, improving availability, latency, cost, and release quality.
• Lead agentic delivery across services, integrations, and release automation while owning production troubleshooting and continuous reliability improvements.

Requirements

• Hands-on production development in Go or Rust and working proficiency in Python, with personal ownership of system design and implementation.
• Substantial systems integration experience, including API contracts, compatibility, concurrency, asynchronous behavior, retries, idempotency, authentication, and distributed-service failures.
• Production MLOps experience with reproducible training or model packaging, artifact tracking, deployment, monitoring, rollback, and batch or online inference for ML or AI workloads on Databricks.
• Production delivery on GCP or Azure using automated tests, CI/CD, identity controls, and observability, plus post-release troubleshooting and service improvement.
• Demonstrated delivery of a substantial feature, service, integration, or engineering tool from proof of concept to production using coding agents such as Codex, Cursor, or equivalents.
• Ability to decompose work, provide repository context and constraints, coordinate parallel tasks, maintain reusable agent instructions, and critically review and integrate generated changes.
• Ability to independently understand, maintain, and debug code; verify tests, security, performance, CI/CD, hardening, rollout, rollback, and production outcomes.
• Bachelor’s degree or equivalent experience in Computer Science or Engineering.

Nice to have

• Experience designing and operating LLM provider integrations, multi-model routing, usage and cost controls, semantic drift monitoring, and evaluation-driven release pipelines.
• Expertise in agent runtimes, durable workflow engines, highly concurrent production systems, and using both Go and Rust across GCP and Azure.

Culture & Benefits

• Hands-on principal-level ownership from architecture and implementation through production operation.
• Emphasis on transparent technical communication, early blocker identification, knowledge sharing, and accountability for released code.
• Benefits are included with the stated pay range.