Staff Software Engineer- AI Platform
Key Skills for This Role
Full Job Posting
Primary Duties:
Identify and develop scalable and performant solutions.
Work across discipline to shape product strategy and execution.
Develop the foundations of code architecture and quality.
Mentor and coach engineers.
Set and uphold the standard for engineering processes to support high-quality engineering.
Minimum Qualifications:
- BS/BTech (or higher) in Computer Science, Engineering or a related field required.
- 8+ years of production-level experience as an engineer building highly scalable systems.
- 4+ years of experience acting as a trusted technical decision-maker in a team setting, solving for 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 at scale.
- Experience with cloud technologies, e.g., AWS, Azure, GCP.
- Experience building continuous integration and continuous development (CI/CD) pipelines.
- Strong familiarity with server-side web technologies (eg: Java, Python, Scala, C#, C++, Go).
- 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, Google Vertex AI, or similar technologies.
- Strong experience with cloud infrastructure, preferably AWS, and technologies such as Kubernetes, containers, and infrastructure as a 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.
- Physical Requirements
Preferred KSAs:
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, Google Vertex AI, or similar technologies.
Strong experience with cloud infrastructure, preferably AWS, and technologies such as Kubernetes, containers, and infrastructure as a 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.
About Aledade
Aledade partners with independent primary care physicians to build and lead accountable care organizations, using technology to improve patient outcomes and reduce costs.
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