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Aledade · Posted 9d ago

Staff Software Engineer- AI Platform

RemoteSenior
Location
🇺🇸 United States
Contract
Full-time
Role
ML engineering
Source
Employer’s own job board (Lever)

Stack

  • Vertex AI
  • LLM
  • SQL
  • Python
  • Scala
  • Java
  • Go
  • C++
  • C#
  • AWS
  • GCP
  • Azure
  • Kubernetes
  • CI/CD

The 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). 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.