Staff Software Engineer, Platform

Gradial•Seattle, WA

15h•$180,000 - $240,000•Onsite

About The Position

Gradial is building the AI-native system of work for enterprise marketing. Our agents turn ideas into live campaigns by executing across the tools, teams, and workflows enterprises already use—from content authoring and campaign assembly to quality assurance and brand compliance. We give marketers and creatives more time to shape brands, understand customers, and create work that moves people. We’re tackling some of the hardest problems in applied AI: building agent harnesses, sandboxed execution environments, and orchestration that enable agents to plan, act, and verify their work reliably at enterprise scale. We’re growing rapidly, winning Fortune 500 and enterprise customers including AWS, T-Mobile, and Prudential. Our $65 million Series C led by Insight Partners is accelerating that momentum. Join us to help define how people and AI agents work together. We move with urgency, reason from first principles, and take ownership from idea to customer impact. You’ll shape the product, own consequential problems, and build systems that some of the world’s leading brands depend on every day. The Role Gradial is looking for a Staff Software Engineer, Platform to serve as a technical leader for the systems and infrastructure our product runs on. You’ll set direction for the platform, lead critical infrastructure initiatives and build the foundations that allow our engineering team to ship quickly and operate reliably as Gradial scales. This is a highly hands-on IC role with significant technical leadership responsibility. You’ll work closely with the CTO and engineering team to identify the highest-leverage platform investments, make key architectural decisions and lead their execution. You’ll help define what great platform engineering looks like at Gradial while building systems that make every engineer more effective.

Requirements

8+ years of professional software engineering experience with significant experience in platform engineering, infrastructure, SRE, DevOps or related areas
Proven ability to serve as a technical lead for complex platform initiatives while remaining deeply hands-on in implementation
Deep expertise in Kubernetes, cloud-native architecture, container orchestration and production infrastructure
Strong experience with infrastructure as code, GitOps, CI/CD workflows and modern deployment practices
Strong command of observability and reliability fundamentals across metrics, logging, tracing, alerting and incident response
Experience designing and operating production infrastructure for rapidly growing products and engineering teams
Ability to identify the highest-leverage platform problems, establish technical direction and drive execution across multiple engineers
Strong technical judgment with a track record of making pragmatic architectural decisions around reliability, scalability, performance and cost
Ability to lead through influence, create alignment and raise the technical bar without relying on formal authority

Nice To Haves

Experience with AI or ML infrastructure, including GPU provisioning, model deployment or compute-intensive workloads
Experience supporting cloud or multi-cloud environments with demanding reliability and scaling requirements
Proficiency with TypeScript or Python for internal tooling and operational automation

Responsibilities

Lead the technical direction of Gradial’s platform across infrastructure, reliability, developer experience, security, performance and cost
Own the reliability, scalability and operational health of our production platform
Lead major platform initiatives from problem definition and architecture through hands-on implementation and production
Evolve our Kubernetes, CI/CD, observability and infrastructure as code foundations as the product and engineering organization scale
Build tooling, abstractions and automation that make it easier for engineers to develop, deploy and operate production systems
Set engineering standards for reliability, service readiness, deployment and operational ownership across the organization
Drive improvements in monitoring, alerting, incident response and observability while turning operational learnings into durable platform improvements
Partner with engineers across the company to identify infrastructure bottlenecks and scaling risks, then prioritize and lead solutions before they become constraints
Provide technical leadership to other engineers through architecture, design reviews, mentorship and hands-on collaboration