Sr. Software Engineer, AI Platform

Hirerising; Phoenix (AZ); On-site; USD 160,000 - 230,000; Full time

Job summary

Hirerising in Phoenix, AZ seeks a Senior Software Engineer for AI Platform Engineering to bridge high-scale systems and frontier AI. You will architect and build Model & Agent Runtimes powering models and autonomous agents across a hybrid-cloud footprint.

This role emphasizes a platform-first mindset, ensuring AI capabilities are scalable, secure, and governed via world-class AgentOps, LLMOps, and MLOps practices.

Qualifications

• Proven experience building scalable back-end systems with containerization.
• Strong understanding of LLM lifecycles and autonomous agents.
• Track record of observability in distributed environments.

Responsibilities

• Architect hosting environments for models and autonomous agents.
• Scale multi-tenant hybrid-cloud infrastructure for diverse environments.
• Implement monitoring, tracing, and automated evaluation in prod.
• Ensure reliability and uptime of AI services as part of a platform team.
• Collaborate with AI teams to reduce friction and accelerate delivery.

Skills

Deep systems expertise

Kubernetes

AI/ML fluency

Observability

Job description

Locations: Phoenix, AZ; Jacksonville, FL; Rochester, MN

As a Senior Software Engineer for AI Platform Engineering, you will bridge the gap between high-scale systems architecture and frontier AI. You will be one of architects and builders of our Model & Agent Runtimes—the specialized engines that govern how models and autonomous agents execute across our hybrid-cloud footprint.

This isn't just about deployment; it’s about a platform-first mindset. You will ensure that AI capabilities are scalable, secure, and governed through world-class AgentOps, LLMOps, and MLOps practices.

• What You’ll DoArchitect the Future of Runtimes: Design and implement high-performance hosting environments for both specialized models and autonomous agents.


• Scale Hybrid-Cloud Infrastructure: Build multi-tenant platform capabilities that support seamless agent and model execution across diverse cloud and on-prem environments.


• Drive Operational Excellence: Implement robust solutions for real-time monitoring, distributed tracing, and automated evaluation of agents & models in production.


• Operational Stewardship: Act as a member of our rotational platform operational team, ensuring the reliability and uptime of critical AIservices.


• Collaborate & Advocate: Partner with cross-functional AI teams to identify system friction, streamlining their workflows and accelerating the delivery of AI-driven value.


• What You’ll BringDeep Systems Expertise: Proven experience building scalable back-end systems, ideally with a focus on containerization and orchestration (Kubernetes).


• AI/ML Fluency: Strong understanding of the lifecycle of LLMs and autonomous agents, including inference optimization and RAG architectures.


• Operational Rigor: A track record of implementing observability (logging, metrics, tracing) in complex, distributed environments.


• Problem-Solving Mindset: The ability to turn abstract AI research into production-grade, hardened platform features.