Platform Engineer

• Provide technical leadership for the cloud platforms, deployment systems, and operational foundations that power enterprise-scale generative AI applications.
• Define and evolve the infrastructure architecture for AI/ML platforms running across AWS, Kubernetes, serverless, and containerized environments.
• Lead platform standards for reliability, scalability, observability, CI/CD, security, and developer enablement, while partnering closely with software engineering, AI engineering, security, and operations teams.
• Define and drive the technical strategy for AI/ML platform infrastructure supporting generative AI applications, LLM integrations, model routing, and enterprise AI services.
• Architect, build, and operate scalable cloud platforms using AWS services such as EKS, ECS Fargate, Lambda, DynamoDB, S3, OpenSearch, Secrets Manager, CloudWatch, ALB, and MWAA.
• Establish reusable infrastructure patterns using CloudFormation, Helm, and Terraform to support reliable multi-environment and multi-region deployments.
• Lead CI/CD architecture using GitHub Actions, reusable workflows, OIDC-based AWS authentication, automated quality gates, deployment promotion, and environment approvals.
• Design and improve observability across AI platforms, including CloudWatch dashboards, logs, alarms, Prometheus/Grafana, OpenSearch, Langfuse, and LLM-specific operational metrics.
• Build platform capabilities for GenAI workloads, including model availability monitoring.
• Partner with software engineering teams to improve deployment reliability, rollback strategies, health checks, autoscaling, load testing, and runtime performance.
• Define and enforce security and compliance practices for infrastructure, including IAM permission boundaries, Secrets Manager usage, secret scanning, audit logging, tagging standards, and change-management controls.
• Provide technical leadership for cost optimization, capacity planning, environment standardization, and operational resilience across development, test, production, and sandbox environments.
• Mentor engineers, review architecture and infrastructure designs, and influence platform engineering practices across teams.

Staff Platform Engineer, AI/ML Infrastructure

• Partner with product engineering teams to identify systems requirements.
• Build and support our cloud-based microservices infrastructure.
• Automate routine processes and remediation tasks.
• Develop, monitor and track Service Level Objectives (SLOs) for the systems under management.
• Proactively troubleshoot, resolve, and plan for issues that typically come from support staff, other engineering teams, and our automated monitoring system.
• Ensure our datastores are healthy and operate at optimal performance levels.
• Contribute to the growth and culture of our engineering team.

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Staff Platform Engineer, AI/ML Infrastructure

Platform Engineer