Aledade · Posted 9d ago
Staff Software Engineer- AI Platform
- 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.