The Role

We’re looking for a Senior Software Engineer to build and scale the backend systems that power our AI agent. This role sits at the intersection of backend engineering, machine learning, and product, and is focused on turning AI capabilities into reliable, production-ready systems.

You won’t be training models, but you will make them work in the real world. You’ll build APIs, services, and data systems that connect LLMs and ML models to user-facing experiences, ensuring performance, reliability, and scalability.

What You’ll Do

• Design and build APIs and backend services that power AI-driven product experiences
• Develop systems that integrate LLMs and ML models into production workflows
• Build and maintain data pipelines supporting training, inference, and evaluation
• Partner closely with ML Engineers, Data Scientists, and Product to ship end-to-end features
• Improve system performance, reliability, and scalability across services
• Contribute to experimentation and feedback loops that improve model and product performance
• Debug complex production issues and drive root cause resolution
• Raise the bar on code quality, system design, and engineering standards

What Success Looks Like

• AI-powered features are reliably delivered through scalable, well-architected backend systems
• ML and LLM capabilities are seamlessly integrated into product experiences with strong performance and uptime
• Clear, maintainable APIs and services enable fast iteration across engineering and product teams
• Systems are designed with strong observability, enabling rapid debugging and improvement
• Engineering decisions consistently balance speed, quality, and long-term scalability

Ideal Background

• 5+ years of experience in software engineering, with strong backend focus
• Strong proficiency in Python and experience building production-grade systems
• Experience designing APIs and service-oriented architectures
• Experience working with ML/AI systems in production environments (LLMs, ranking, recommendations, or similar)
• Familiarity with databases (SQL and/or NoSQL) and data-intensive systems
• Experience with cloud platforms (AWS, GCP, or Azure) and modern infrastructure
• Exposure to containerization and orchestration (Docker, Kubernetes)
• Ability to operate in ambiguity and take ownership of loosely defined problems
• Strong product mindset with focus on real user outcomes
• Clear communication and ability to collaborate across engineering, ML, and product

Compensation & Benefits

The expected base salary range for this role is $200,000–$225,000 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.