Senior DevOps & AI

Role: Senior DevOps & AI Engineer: Agentic AI

Work: EST/CST Time Zones | Remote

The Opportunity

We're partnering with a fast-growing, tech-led business in the insurance and financial services space. They're hiring an Infrastructure & AI Engineer to be the dedicated infrastructure owner for a new Agentic AI squad.

This is a hands-on role covering both DevOps and AI. You'll own the infrastructure, automation and deployment tools that let the engineering team build and ship quickly. You'll also keep the AI agents and models reliable, observable and cost-effective in production.

You'll sit inside the product squad, working with engineers and product teams day to day. This isn't a central infrastructure function or a ticket queue.

What You'll Own

• The build, deployment and runtime infrastructure for the Agentic AI squad
• CI/CD pipelines, infrastructure-as-code and cloud environments
• Automating processes and tooling so engineers can deploy and iterate on their own
• AI/ML observability across production agents and models, covering latency, cost, failure rates, output quality and model drift
• Monitoring, alerting and guardrails that catch degraded agent performance or unexpected infrastructure and model spend
• Setting up solid operational practices for running agentic AI systems in production
• Troubleshooting, improving and scaling production services with the engineers
• On-call ownership for the squad's services, plus clear escalation and support processes

What We're Looking For

You'll need to be strong in both infrastructure engineering and production AI operations.

Essential:

• Strong experience across CI/CD, Infrastructure as Code and cloud operations
• Experience running and supporting production cloud infrastructure
• Comfortable as an embedded engineer in a fast-moving product squad
• Proven experience running AI or ML systems in production
• A strong grasp of the operational challenges of AI/ML workloads, beyond traditional application infrastructure
• Comfortable taking ownership and working directly with engineers under delivery pressure
• Willing to own production services and join an on-call rotation

Nice to Have:

• Agent-specific observability or monitoring
• Building or running AI/ML evaluation pipelines
• LLM cost management and optimization
• Previous experience as an embedded DevOps / Platform Engineer in a small team
• Experience with agentic AI systems, LLMs or AI platforms