Autonomous AI Production Engineer for Enterprise Deployments

ResolveAi; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Medical Insurance

Housing Stipend

Unlimited PTO

Visa Sponsorship & Immigration Support

401(k) Plan

Parental Leave

Tech Benefit Stipend

Daily in-office Lunches and Dinners

Job summary

Resolve AI is seeking engineers to own enterprise deployments and build production-grade AI agents that integrate with customers’ infra. You will work directly with large engineering teams to deploy, monitor, and optimize outcomes across Kubernetes, cloud platforms, and observability stacks.

The role emphasizes ownership, go-to-market collaboration, and delivering tangible improvements in how engineering teams operate with AI-powered workflows.

Qualifications

• Strong software engineering fundamentals and production-grade software experience.
• Excellent customer-facing communication and ability to build trusted relationships with engineers and leaders.
• Ability to drive customer outcomes by expanding usage and removing blockers.
• Familiarity with production infrastructure including Kubernetes, cloud platforms, and distributed systems.

Responsibilities

• Own enterprise deployments end-to-end with large engineering orgs.
• Build custom agents, integrations, and features for customer-specific problems.
• Understand customer infrastructure and tooling (Kubernetes, clouds, observability, incident tools).
• Drive technical adoption and expansion with customer teams and new use cases.
• Bridge customers and core engineering to inform roadmap and scalable capabilities.
• Own outcomes and deliver measurable improvements in engineering operations.
• Operate with urgency and ownership in ambiguous, challenging environments.

Skills

Python

Go

TypeScript

Kubernetes

Docker

AWS

Tools

Kubernetes

Docker

AWS

GCP

Job description

Resolve AI is seeking engineers to own enterprise deployments and build production-grade AI agents that integrate with customers’ infra. You will work directly with large engineering teams to deploy, monitor, and optimize outcomes across Kubernetes, cloud platforms, and observability stacks.

The role emphasizes ownership, go-to-market collaboration, and delivering tangible improvements in how engineering teams operate with AI-powered workflows.