Staff Software Engineer- AI Platform

Aledade PBC

18h

About The Position

As a Staff Software Engineer on Aledade's AI Core Platform team, you will help build and operate shared infrastructure that enables applications and AI agents across the company to access foundation models securely and reliably. You will develop platform capabilities for model access, including model gateways, cloud AI services, provider integrations, routing and fallback, usage controls, observability, reliability, and model governance.

The role focuses on production platform systems across their full lifecycle, including architecture, scalability, failure modes, security, observability, operational readiness, cost, and developer experience. You will evolve the platform as AI adoption grows, building reusable, self-service capabilities rather than one-off solutions. You will collaborate with engineers, product partners, security and infrastructure teams, and teams building AI applications and agents. The position calls for pragmatic technical decision-making in ambiguous problem spaces and the development of secure, maintainable, observable, and resilient systems.

Requirements

• Bachelor's degree or higher in Computer Science, Engineering, or a related field.
• 8+ years of production-level engineering experience building highly scalable systems.
• 4+ years of experience acting as a trusted technical decision-maker in a team setting, balancing short-term and long-term business value.
• 4+ years of experience working with SQL or other database querying languages on large, multi-table data sets.
• Experience architecting, developing, and deploying large-scale distributed systems.
• Experience with cloud technologies such as AWS, Azure, or GCP.
• Experience building continuous integration and continuous development (CI/CD) pipelines.
• Strong familiarity with server-side web technologies such as Java, Python, Scala, C#, C++, or Go.

Nice To Haves

• Experience building or operating production platform infrastructure, distributed systems, developer platforms, or other high-availability shared services.
• Experience with LLM infrastructure, model gateways, foundation model APIs, or managed AI platforms such as AWS Bedrock, Azure OpenAI, or Google Vertex AI.
• Strong cloud infrastructure experience, preferably with AWS, and technologies such as Kubernetes, containers, and infrastructure as code.
• Experience designing observability and operational practices for production systems, including metrics, distributed tracing, logging, alerting, SLOs, dashboards, and failure handling.
• Experience designing APIs and self-service platform capabilities used by other engineering teams.
• Experience with identity, access control, secrets management, security, and governance for shared infrastructure.
• Experience with cost management, usage attribution, quotas, budgets, or capacity management for shared platforms.
• Experience operating systems that handle sensitive or regulated data.
• Ability to evaluate architectural tradeoffs across reliability, performance, security, cost, scalability, and developer experience.

Responsibilities

• Identify and develop scalable and performant solutions.
• Work across disciplines to shape product strategy and execution.
• Develop the foundations of code architecture and quality.
• Mentor and coach engineers.
• Set and uphold engineering-process standards that support high-quality engineering.
• Build and operate shared infrastructure for secure and reliable access to foundation models.
• Develop platform capabilities such as model gateways, cloud AI services, provider integrations, routing and fallback, usage controls, observability, reliability, and model governance.
• Evolve reusable, self-service platform capabilities as AI adoption grows across the company.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior