Staff Software Engineer- AI Platform

OpenKrill; United States; Remote; USD 180,000 - 260,000; Full time

Job summary

Aledade is seeking a Staff Software Engineer for the AI Core Platform team to help build and operate shared infrastructure enabling applications and AI agents to securely access foundation models. You will own platform capabilities behind model access, including gateways, cloud services, provider integrations, routing, governance, and observability.

You will work with engineers, product partners, security, and infrastructure teams to evolve a scalable, secure, and observable platform.

Qualifications

• 8+ years of production-level experience building scalable systems.
• 4+ years as a trusted technical decision-maker.
• 4+ years of experience querying large multi-table datasets with SQL.
• Experience architecting, developing, and deploying large-scale distributed systems at scale.
• Experience with cloud technologies (AWS, Azure, GCP).
• Experience building CI/CD pipelines.
• Strong familiarity with server-side web technologies (Java, Python, Scala, C#, C++, Go).

Responsibilities

• 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.

Skills

Distributed systems

Technical decision-making

SQL querying

CI/CD pipelines

Cloud platforms

Server-side web tech

Education

BS/BTech in CS or related field

Tools

AWS

GCP

Azure

Kubernetes

Docker

Infrastructure as Code

Job description

As a Staff Software Engineer on Aledade's AI Core Platform team, you will help build and operate the shared infrastructure that enables applications and AI agents across Aledade to securely and reliably access foundation models.

You will work on the platform capabilities behind model access, including model gateways, cloud AI services, provider integrations, routing and fallback, usage controls, observability, reliability, and model governance.

We're looking for engineers who think beyond implementing individual features and consider the full lifecycle of production platform systems: architecture, scalability, failure modes, security, observability, operational readiness, cost, and developer experience. You will help evolve the platform as AI adoption grows across Aledade, building reusable and self-service capabilities rather than one-off solutions.

You will work closely with engineers, product partners, security, infrastructure teams, and teams building AI applications and agents. Successful engineers in this role are comfortable operating in ambiguous problem spaces, making pragmatic technical decisions, and building secure, maintainable, observable, and resilient systems.

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).

Preferred KSAs:AI Infrastructure & Model Platform:

• - 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:Sitting for prolonged periods of time. Extensive use of computers and keyboard. Occasional walking and lifting may be required.