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About Wizard
Wizard is the top-performing AI Shopping Agent, delivering the best products from across the web with unmatched accuracy, quality, and trust.
The RoleWe’re hiring a DevOps Engineer to own the core infrastructure, deployment systems, and operational foundations that support Wizard’s application and ML teams. This role is focused on cloud infrastructure, CI/CD, reliability, security, and developer enablement.
You will not be responsible for building or owning ML pipelines or model logic. Instead, you’ll ensure the underlying platform is stable, secure, observable, and easy for engineering teams to build on.
This is a hands-on role with real ownership. You’ll shape how systems are deployed, monitored, secured, and scaled as Wizard moves deeper into production and growth.
What You’ll Do- Design, build, and maintain secure, scalable cloud infrastructure
- Own CI/CD pipelines and deployment workflows across services and environments
- Improve reliability, availability, and performance through monitoring, alerting, and incident response practices
- Partner with application and ML teams to reduce friction in build, test, and deploy workflows
- Implement infrastructure-as-code and automation to reduce manual operational work
- Establish and document best practices for infrastructure, security, and operational readiness
- Support production systems through on-call rotation and continuous improvement
- Ensure compliance with security standards and proactively manage risk
- 5+ years of experience in DevOps, Infrastructure, or Platform Engineering
- Strong experience running production systems in AWS, GCP, or Azure
- Hands-on experience with CI/CD tooling and modern deployment practices
- Solid understanding of networking, security, observability, and reliability concepts
- Proven ability to enable engineering teams through good tooling and clear standards
- Experience working alongside ML or data teams, without owning model development
- Bachelor’s degree in Computer Science or a related field, or equivalent experience
- Experience with Kubernetes and container orchestration
- Familiarity with Python or TypeScript
- Exposure to supporting ML workloads from an infrastructure perspective
- Experience in fast-moving startup environments
The expected base salary range for this role is $185,000 – $210,000 USD, and will vary based on skills, experience, role level, and geographic location. Final compensation will be determined by considering these factors alongside overall role scope and responsibilities.
In addition to base salary, Wizard offers:
- Equity in the form of stock options
- Medical, dental, and vision coverage
- 401(k) plan
- Flexible PTO and company holidays
- Fully remote work within the United States
- Periodic company offsites and team gatherings
Wizard is committed to fair, transparent, and competitive compensation practices.
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
