Staff Infrastructure Software Engineer - AI Platform

The Role

We are currently seeking a Staff Software Engineer to join the AI Platform team to drive the design, architecture, and production posture of Addepar’s AI Platform and our products and solutions. This team is at the center of Addepar's mission to integrate AI across our product suite and is growing quickly.

This role focuses on building a scalable platform and infrastructure to power deep, rich AI capabilities and products. As the AI platform expands, you will be a central architect of the "Core Platform" layer – building the managed services, serving infrastructure, observability, and cross-platform integrations that turn experimental AI capabilities into scalable production software. This includes productionizing the cutting edge of the latest AI developments like agents, MCP, computer use, etc; alongside designing and automating the operational backbone of Addepar's AI stack. 

The ideal candidate will play a staff, leading role in defining, implementing, and strategically evolving Addepar’s AI Production infrastructure and the products it delivers. This includes designing, deploying, monitoring, automating, and optimizing all operational aspects of Addepar's AI platform with a focus on reliability, scalability, and efficiency.

Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position.

What You’ll Do

• Design and build the production runtime for LLM-based agents and products, creating the services and infrastructure that serve autonomous agents.
• Develop deep application-level knowledge to proactively inform and influence requirements, constraints and best practices for implementing composable, complex AI systems.
• Lead the design, implementation, and automation of production infrastructure on a variety of cloud environments (Kubernetes/Databricks), to enable us to ship and scale AI features instantly.
• Evangelize and promote disciplined, best engineering practices to enforce strong production hygiene and culture.
• Initiate and lead collaborations with cross-functional teams to identify and resolve complex application or infrastructure issues, serving as a technical subject matter expert.
• Architect, build, and maintain advanced, automated CI/CD pipelines e.g. using Jenkins, ArgoCD, AWS CodeBuild/Pipeline, GitHub Actions, or similar, establishing best practices for deployment strategies (e.g., blue/green, canary).
• Develop systems and best practices monitoring, alerting, and troubleshooting of our probabilistic and AI-driven systems and broader software stack.

Who You Are

• Extensive experience as a Software/Backend Engineer, with a track record of taking on increasing responsibility.
• Experience across the full product lifecycle: designing, implementing, shipping, scaling, operationalizing, and maintaining technology/SaaS products.
• Exceptional Programming skills and fundamentals in Python/Go/Java, with a proven track record of building large scale production systems. 
• Proficient experience with diverse compute environments including microservices (K8s), Databricks and serverless architectures (e.g. AWS Lambda).
• Demonstrable experience leading initiatives with infrastructure-as-code tools such as Terraform in complex, multi-account environments.
• Proficient experience with comprehensive monitoring and alerting stacks (e.g. Prometheus/Grafana/Sentry/cloud-native tools), with a focus on observability strategy.
• Excellent interpersonal and communication skills to effectively collaborate with multi-functional teams, articulate complex technical concepts, and influence outcomes.
  
  
• Bonus points/Nice to haves: 
  • Extensive experience with Databricks (Unity Catalog, Model Serving, Jobs).
  • Demonstrable experience writing and contributing to significant systems automation tooling or open-source projects is a strong plus.
  • Specific experience with LLMs and agentic systems and associated technologies such as Langchain, Vector DBs, or MLFlow.
  • Exposure to industry practices in financial services or other highly regulated data environments is a plus.