Remote job
Senior Software Engineer II- AI Platform
Job details
About this role
Role overview
Build and operate shared platform services that let application teams and AI agents access foundation models securely and reliably. The work spans model gateways, cloud AI services, provider integrations, routing, usage controls, observability, reliability, and governance. You will shape reusable, self-service capabilities and make decisions across the full lifecycle of production systems, working with engineering, product, security, infrastructure, and AI application teams.
Responsibilities
- Design and implement scalable, performant platform services for model access and AI workloads. - Develop technical roadmaps with engineering, product, and other stakeholders, using Agile processes. - Consider system architecture, security, cost, failure handling, operational readiness, and developer experience as the platform evolves. - Coach engineers through mentoring and detailed pull request reviews, while incorporating feedback on your own work.
Requirements
- A bachelor’s degree or higher in computer science, engineering, or a related field. - At least six years building full-stack web applications on cross-functional teams. - At least three years querying large, multi-table datasets using SQL or a similar language. - At least three years serving as a trusted technical decision-maker and balancing near-term and longer-term business value. - At least three years coaching other engineers.
Nice to have
- Experience operating production platforms, distributed systems, developer platforms, or other highly available shared services. - Familiarity with foundation model APIs, model gateways, or managed AI services, and cloud infrastructure such as AWS, Kubernetes, containers, and infrastructure as code. - Experience with production observability and operations, including metrics, tracing, logs, alerts, service objectives, dashboards, and failure handling. - Background designing APIs and self-service tools, or managing identity, access, secrets, security, and governance for shared infrastructure. - Experience managing platform costs, quotas, usage attribution, capacity, or systems handling sensitive or regulated data.