The Role

We are currently seeking a Staff Software Engineer, Infrastructure to join the AI Platform team that powers seamless insights and interaction through natural language and data intelligence across our AI products.

As a Staff Software Engineer, you’ll architect, build, and operate the backend and platform systems that power AI Platform. You’ll work across service design, distributed systems, cloud infrastructure, event-driven processing, observability, CI/CD, and production reliability, helping shape the technical direction of a platform that supports scalable, client-facing AI experiences.

This role requires a strong software engineering foundation combined with deep infrastructure and systems thinking. We are looking for an engineer who can write high-quality production code, make sound architectural tradeoffs, and own platform capabilities end-to-end — not someone focused only on scripting, cloud configuration, or infrastructure tooling in isolation.

You will collaborate closely with frontend, product, and AI/ML engineers to deliver reliable, secure, and scalable systems that align with Addepar’s standards of performance, resilience, and trust.

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, build, and operate backend services and infrastructure that power AI Platform products.
• Write high-quality production code for platform and service layers, with strong emphasis on maintainability, reliability, and performance.
• Architect and evolve distributed systems that support AI Platform capabilities such as real-time interactions, asynchronous processing, and secure data workflows.
• Build and extend cloud-native infrastructure across core services, networking, storage, identity, and observability layers.
• Design and maintain infrastructure as code using Terraform, including reusable modules, environment management, and drift-safe workflows.
• Build and operate Kubernetes/EKS-based services, including deployment strategies, health checks, scaling configuration, and containerization workflows.
• Design and improve CI/CD pipelines, release workflows, and engineering productivity systems.
• Build and maintain asynchronous and event-driven systems using queues, RPC/service communication, and resilient failure-handling patterns.
• Design and evolve relational and NoSQL data models, including schema design, migrations, replication, and access patterns.
• Build and maintain observability across metrics, logs, tracing, dashboards, and alerting.
• Apply secure-by-default engineering practices across IAM, secrets, encryption, network isolation, and production operations.
• Mentor engineers through code review, design review, incident reviews, and technical guidance.
• Drive technical decisions that improve platform reliability, scalability, developer productivity, and long-term system health.

Who You Are

• Bachelor’s degree in Computer Science, Engineering, or related technical field (or equivalent practical experience).
• At least 8+ years of professional software engineering experience, including significant experience in backend, infrastructure OR platform oriented work.
• Strong proficiency in at least one production backend language such as Python, Go, OR Java and the ability to work effectively across a polyglot environment.
• Strong software engineering fundamentals, including system design, debugging, code quality, testing, and operational ownership.
• Deep hands-on experience with cloud infrastructure in production environments.
• Strong experience with infrastructure-as-code workflows such as Terraform or equivalent tools.
• Experience with Kubernetes/EKS, Docker, and modern deployment practices.
• Experience designing or extending CI/CD pipelines in production environments.
• Experience with distributed systems, microservice communication, message queues, asynchronous processing, and failure handling.
• Experience with both relational and NoSQL database design in production systems.
• Strong observability and production-debugging skills.
• Strong communication, collaboration, and mentoring skills.
• Ability to operate as a software engineer first: we are not looking for someone who is only strong in scripting, cloud configuration, or infrastructure tooling without corresponding depth in production software engineering.

Bonus

• Experience with AI/ML platform tooling such as Databricks, Spark, MLflow, or model-serving systems.
• Experience with real-time streaming or WebSocket-based systems at scale.
• Experience with multi-region architectures, data residency, or failover design.
• Experience in fintech or other highly regulated environments.
• Experience optimizing platform cost, performance, and reliability tradeoffs at scale.