AI Ops Senior Backend Engineer

Commerce•Austin, TX

4d•Hybrid

About The Position

Welcome to the Agentic Commerce Era At Commerce, our mission is to empower businesses to innovate, grow, and thrive with our open, AI-driven commerce ecosystem. As the parent company of BigCommerce, Feedonomics, and Makeswift, we connect the tools and systems that power growth, enabling businesses to unlock the full potential of their data, deliver seamless and personalized experiences across every channel, and adapt swiftly to an ever-changing market. We believe in harnessing AI responsibly to unlock new possibilities, and we’re looking for individuals who use it intentionally to solve problems, accelerate outcomes, and expand what’s possible in their role. Our purpose is to help businesses confidently solve complex commerce challenges so they can build smarter, adapt faster, and grow on their own terms. If you want to be part of a team of bold builders, sharp thinkers, and technical trailblazers who shape the future of commerce, this is the place for you. We are looking for a Senior Backend Engineer to join our AI Operations organization and partner closely with the Data Solutions team to design, build, and scale the systems that power our AI-driven operations. In this role, you’ll help shape the next generation of AI-native products and automation frameworks—transforming ideas into intelligent, intuitive, and impactful tools that enable teams across the company to work smarter and faster. You'll own the product lifecycle end-to-end — from stakeholder discovery and solution design through build, deployment, and ongoing monitoring. You'll implement novel AI technologies, rapidly prototype applications, and ensure seamless integration with our data infrastructure. You’ll be part of a fast-moving, collaborative team that values experimentation, innovation, and craftsmanship. Working alongside analysts, engineers, and operations leaders, you’ll have the autonomy to prototype new concepts, own end-to-end product delivery, and play a key role in expanding how Commerce leverages AI to drive efficiency and business growth.

Requirements

5+ years of professional experience as a backend engineer, with a proven track record of building and scaling production-grade applications.
You architect systems end-to-end, from data flow to deployment.
Demonstrated experience building AI-driven products incorporating agent orchestration, MCP servers, RAG patterns, structured outputs, evals, and the operational realities of running AI in production (latency, cost, prompt drift, hallucination mitigation).
You use AI development tools daily and have opinions about how to use them well.
Proficient in cloud environments like AWS, GCP, or Vercel.
You design systems with security in the forefront.
You understand AI failure modes, research emerging risks, and incorporate guardrails and evals from the start.
Adept at working across technical and business functions, balancing rapid prototyping with long-term architecture planning.
Thinks beyond code to design systems and experiences that are scalable, maintainable, and valuable to end users.
Thrives in fast-moving environments, comfortable testing new ideas quickly while maintaining high standards for quality and reliability.

Nice To Haves

Actively experiments with emerging AI tools and techniques. Tries the betas, conducts the research, and brings back what works—turning curiosity into practical improvements for the team and the systems you build.

Responsibilities

Develop secure, high-performance services that connect data systems, AI models, and business applications into a cohesive, scalable ecosystem.
Collaborate with stakeholders to translate strategic goals into technical requirements, prototypes, and production-ready solutions.
Own the product lifecycle end-to-end — including discovery, solution design, architecture, build, deployment, monitoring, and stakeholder management.
Design, build, and maintain AI applications that enable automation, streamline workflows, and extend AI capabilities across internal teams.
Rapidly prototype and iterate on new applications and features, experimenting with AI integrations and automation concepts to drive measurable business impact.
Implement engineering best practices for performance optimization, maintainability, and data security across all deployed systems.
Partner with a broader team of data engineers and analysts to ensure shared ownership of systems, clear priorities, and strong technical support.