Top Hybrid DevOps & Platform Engineering Jobs in Boston, MA

The Senior IT Support Engineer will bridge 2nd and 3rd line support, mentor junior staff, manage device fleets, and build self-service tools.

The Platform Administrator IV leads platform changes, optimizes performance, automates processes, and mentors junior staff while ensuring platform reliability and compliance.

As a Senior DevOps Engineer at WHOOP, you will enhance application infrastructure to ensure high performance, scalability, and security while mentoring engineering teams.

The role involves designing and managing secure cloud infrastructure on AWS, automating security practices, and collaborating with various teams to improve developer workflows and ensure compliance. Key tasks include IAM management, implementing automation tools, and participating in incident response.

The Cloud Engineer role involves developing configurations in YAML and JSON, building monitoring solutions, maintaining software applications, and writing custom scripts for various environments.

Lead design and implementation of AWS-based infrastructure and CI/CD for a secure, scalable clinical data platform. Build IaC, automate releases and testing, operationalize MLOps, mentor engineers, troubleshoot distributed production issues, and ensure observability, compliance, and disaster recovery.

As a Principal Engineer for Core Infrastructure at Klaviyo, you will architect and enhance the Kubernetes platform and CI/CD pipelines, improve developer velocity, and ensure operational excellence while incorporating AI tools for automation and incident response.

Design, architect, and operate secure cloud infrastructure (primarily Azure) at scale. Lead Kubernetes implementations and platform reliability, mentor junior engineers, troubleshoot and perform root-cause analysis, and drive cloud infrastructure projects from requirements through technical execution.

Lead the technical architecture and execution of cloud-based HPC platforms across AWS/GCP. Drive IaC, automation, monitoring, and reliability for high-throughput, low-latency HPC and ML workloads. Define standards, recommend technologies (accelerators, storage, schedulers), mentor engineers, manage vendor/cloud partner engagements, and optimize performance, cost, and security of the scientific computing platform.

Lead design, development, deployment, and support of foundational AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, and observability. Optimize large-scale AI performance (cost, latency, throughput), partner cross-functionally, and contribute to technical vision and roadmap.

Design and develop cloud-scale software, maintain cloud infrastructure, ensure compliance, and collaborate with teams to deliver high-quality applications.