Senior AI Engineer in Calabasas, California at Get Covered LLC

About Get Covered LLC

We provide cost-effective coverage with just a few clicks — satisfying residents, property managers, agencies, and distribution partners with a process that is as simple and touchless as possible.

Senior AI Engineer

Location: Onsite – Calabasas, CA (5 days in Office, This is not a remote role.)

Experience Required: 3 years

Education: Bachelor's degree in Computer Science or related field, or equivalent practical experience

About the Role

We're looking for an AI Engineer who lives at the intersection of AI, full stack development, and its infrastructure. Someone who can architect intelligent systems from the application layer all the way down to the deployment substrate.

This is a high-autonomy role in an amazing team of builders: you'll get along with your peers, and set the technical direction for AI-powered applications, make the architectural calls, and turn ambiguous business problems into production systems that move the needle.

You’ll scope your own work, unblock yourself, and ship without needing a detailed playbook.

You'll work directly with product, engineering, and operations leadership to decide where AI creates real leverage, and then build it. If you're equally comfortable designing a full stack app, multi-agent LLM pipeline and wiring up EKS clusters, and CI/CD workflows, this role is for you.

We also want someone with genuine curiosity, a tinkerer who stays ahead of the curve, experiments with new tools and models before they're mainstream, and brings that energy to the team. You should be able to hit the ground running on day one with minimal hand-holding.

This position is fully onsite at our Calabasas, CA office.

What You'll Do

• Own the design and architecture of AI-powered applications, tools, and workflows from concept to production.
• Identify high-impact opportunities to apply AI across the company and drive them from idea to deployment, end to end.
• Set engineering standards, lead code reviews, define best practices, and raise the bar for quality, security, and maintainability across both AI and infrastructure layers.
• Architect and integrate APIs for secure, scalable data access and exchange.
• Code and build production-grade features on top of LLMs, with a focus on reliability, evaluation, and cost-efficiency.
• Own performance, scalability, and availability, troubleshoot complex issues and design for resilience at both the application and infrastructure level.
• Deploy and manage applications on AWS using modern CI/CD pipelines, with strong practices around observability, rollback, and zero-downtime deployments.
• Partner with cross-functional teams and influence the broader AI roadmap and technical strategy of the organization.

What We're Looking For

• Strong proficiency across a modern application stack:
• • Programming & Frameworks: Python plus one or more of React, Next.js, Node.js/Express.js, or Ruby on Rails
  • Databases: SQL (MySQL, PostgreSQL)
  • CI/CD: GitHub Actions or equivalent, with real deployment ownership
• 3 years of professional experience in software engineering, with significant recent work in AI/ML or LLM-powered applications.
• Demonstrated ownership of systems in production, you've designed, shipped, and maintained real software, not just prototypes.
• Deep expertise in AI engineering workflows and prompt design, with strong intuition for what LLMs can and can't do reliably.
• Technical architecture experience,you understand how the pieces fit together and can make informed decisions about which services to use and why.
• Hands-on experience building with frontier AI tools such as Claude, OpenAI, and Cursor.
• Strong command of RESTful API design and integration.
• The ability to move autonomously, you scope your own work, unblock yourself, and ship without needing a detailed playbook.
• Sound engineering judgment, you know when to optimize, when to ship, and how to balance tradeoffs across cost, speed, and reliability.
• Genuine curiosity about the AI space, you follow new model releases, experiment with emerging tools, and bring fresh ideas to the team.
• Excellent communication skills and the ability to collaborate across technical and non-technical teams.