Staff Software Engineer – AI Platform

🕒 October 22

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

🤖 AI Engineer

👻 Ghost score 10%

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Aledade, Inc.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2014

🏥 Healthcare

⚕️ Healthcare Insurance

🏢 Enterprise

Healthcare • Healthcare Insurance • Enterprise

Aledade, Inc. is a public benefit corporation that operates as the largest network of independent primary care practices in the United States. The company specializes in Accountable Care Organizations (ACOs), which help primary care practices and health centers improve patient outcomes and generate sustainable revenue through value-based care solutions. Aledade offers data insights, support, and business solutions to achieve sustainability and clinical autonomy. It collaborates with a wide range of healthcare providers, including primary care practices, community health centers, and network ACOs, ensuring improved quality of care and patient satisfaction. With operations in 45 states and affiliations with over 20,000 clinicians serving more than 2. 5 million patients, Aledade is committed to reducing care fragmentation and enhancing the overall quality of life for clinicians and patients alike.

📋 Description

• Build and operate shared infrastructure enabling Aledade applications and AI agents to securely and reliably access foundation models • Develop platform capabilities including model gateways, cloud AI services, provider integrations, routing and fallback, usage controls, observability, reliability, and model governance • Consider the full lifecycle of production platform systems, including architecture, scalability, failure modes, security, operational readiness, cost, and developer experience • Evolve the platform as AI adoption grows, building reusable and self-service capabilities rather than one-off solutions • Identify and develop scalable and performant solutions • Work across disciplines to shape product strategy and execution • Develop foundations of code architecture and quality • Mentor and coach engineers • Set and uphold engineering process standards supporting high-quality engineering • Collaborate with engineers, product partners, security, infrastructure teams, and AI application and agent teams

🎯 Requirements

• 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 such as Java, Python, Scala, C#, C++, or 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 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 • Sitting for prolonged periods of time • Extensive use of computers and keyboard • Occasional walking and lifting may be required

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