Staff Software Engineer - AI Platform

Responsibilities:

• Design, build, and operate backend services and infrastructure that power AI platform products.
• Write high-quality production code for platform and service layers, with strong emphasis on maintainability, reliability, and performance.
• Architect and evolve distributed systems that support AI platform capabilities such as real-time interactions, asynchronous processing, and secure data workflows.
• Build and extend cloud-native infrastructure across core services, networking, storage, identity, and observability layers.
• Design and maintain infrastructure as code using Terraform, including reusable modules, environment management, and drift-safe workflows.
• Build and operate Kubernetes/EKS-based services, including deployment strategies, health checks, scaling configuration, and containerization workflows.
• Design and improve CI/CD pipelines, release workflows, and engineering productivity systems.
• Build and maintain asynchronous and event-driven systems using queues, RPC/service communication, and resilient failure-handling patterns.
• Design and evolve relational and NoSQL data models, including schema design, migrations, replication, and access patterns.
• Build and maintain observability across metrics, logs, tracing, dashboards, and alerting.
• Apply secure-by-default engineering practices across IAM, secrets, encryption, network isolation, and production operations.
• Mentor engineers through code review, design review, incident reviews, and technical guidance.
• Drive technical decisions that improve platform reliability, scalability, developer productivity, and long-term system health.

Requirements:

• Bachelor's degree in computer science, engineering, or a related technical field, or equivalent practical experience.
• 8+ years of professional software engineering experience, including significant experience in backend, infrastructure, or platform-oriented work.
• Strong proficiency in at least one production backend language, such as Python, Go, or Java, and the ability to work effectively across a polyglot environment.
• Strong software engineering fundamentals, including system design, debugging, code quality, testing, and operational ownership.
• Deep hands-on experience with cloud infrastructure in production environments.
• Strong experience with infrastructure-as-code workflows such as Terraform or equivalent tools.
• Experience with Kubernetes/EKS, Docker, and modern deployment practices.
• Experience designing or extending CI/CD pipelines in production environments.
• Experience with distributed systems, microservice communication, message queues, asynchronous processing, and failure handling.
• Experience with both relational and NoSQL database design in production systems.
• Strong observability and production-debugging skills.
• Strong communication, collaboration, and mentoring skills.
• Ability to operate as a software engineer first, with depth in production software engineering beyond scripting, cloud configuration, or infrastructure tooling alone.

Nice to have:

• Experience with AI/ML platform tooling such as Databricks, Spark, MLflow, or model-serving systems.
• Experience with real-time streaming or WebSocket-based systems at scale.
• Experience with multi-region architectures, data residency, or failover design.
• Experience in fintech or other highly regulated environments.
• Experience optimizing platform cost, performance, and reliability tradeoffs at scale.