Top Hybrid DevOps & Platform Engineering Jobs in Boston, MA

Lead the production infrastructure organization to define platform primitives (compute, storage, networking, observability), drive reliability (SLOs/SLIs, incident management, capacity planning), create golden paths and cost-effective frameworks, mentor and scale teams, collaborate cross-functionally on platform investments, and apply AI to improve infrastructure operations and developer productivity.

Partner with Field and Product teams to design and implement LLM observability architectures, build proofs-of-concept, produce technical collateral, and advise customers to drive adoption and product feedback.

Lead design and implementation of LLM observability features: prototype and scale product capabilities for tracing, evaluating, and debugging generative AI systems. Work cross-functionally to influence architecture, mentor engineers, prioritize customer pain points, and drive product and engineering decisions for reliable, high-performance AI observability.

The role involves leading the implementation of cloud solutions, evaluating cloud application requirements, mentoring team members, and ensuring high standards in deployments while analyzing complex issues.

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

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.