Staff Software Engineer – AI Platform

Aledade, Inc.

. Build and operate shared infrastructure enabling Aledade applications and AI agents to securely and reliably access foundation models .

Posted 10/22/2026full-timeRemote • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating scalable, high-availability shared infrastructure for AI applications, with a strong focus on cloud technologies, observability, and security. Proven ability to mentor engineers and uphold engineering standards while collaborating across disciplines to drive product strategy.

Highest-signal resume keywords

Cloud Technologies (AWS, Azure, GCP)Large-Scale Distributed Systems ArchitectureCI/CD Pipeline DevelopmentServer-Side Web Technologies (Java, Python, Scala, C#, C++, Go)Observability and Operational Practices Design

ATS Keywords

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Hard Skills

SQLDatabase Querying LanguagesInfrastructure as CodeKubernetesContainersModel GatewaysFoundation Model APIsManaged AI PlatformsAPI DesignCost Management

Soft Skills

MentoringCollaborationTechnical Decision-Making

Tools & Technologies

AWS BedrockAzure OpenAIGoogle Vertex AIDistributed TracingLoggingAlertingSLOsDashboards

Industry Keywords

Production Platform InfrastructureHigh-Availability ServicesOperational ReadinessSecurity and GovernanceScalability

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaKubernetesPythonScalaSQLC++Go

About the role

Key responsibilities & impact

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

What you’ll need

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