Top Tech Jobs & Startup Jobs in Boston, MA

Designs and publishes networking architectures for large-scale GPU clusters and AI infrastructure. Responsibilities include InfiniBand and RoCEv2 fabrics, multi-tenant isolation, Linux and Kubernetes networking, KubeVirt, hybrid connectivity, research, automation, benchmarking, proofs of concept, customer engagements, partner collaboration, technical writing, and conference presentations.

Owns complex, client-facing cloud and AI engagements from pre-sales scoping through delivery and acceptance. Responsibilities include planning, stakeholder coordination, risk and dependency management, client communication, commercial oversight, change orders, vendor management, executive reporting, and identifying follow-on opportunities. The role manages multiple engagements or large multi-workstream programs involving enterprise customers, cloud providers, engineering teams, and third-party vendors.

Owns end-to-end global recruitment for technical, product, business, and go-to-market roles. Responsibilities include direct sourcing, pipeline development, hiring-manager advising, talent-market research, candidate experience management, ATS workflow administration, and independently managing multiple searches across distributed teams and time zones.

Lead an engineering organization building secure enterprise container and Kubernetes platforms. Define technical strategy, improve platform resilience and operational excellence, embed security throughout the SDLC, balance feature delivery with stability, hire and develop engineering talent, and collaborate with product leaders, executives, and enterprise customers.

Design and build Kubernetes-based LLM serving infrastructure, including GPU scheduling, scaling, model lifecycle management, Helm packaging, enterprise and offline deployments, API integrations, and production observability. Develop across a multi-service Go codebase, contribute design documentation and reviews, and help guide engineering direction. The role requires strong Kubernetes, distributed systems, CI/CD, and infrastructure-as-code expertise, with GPU, inference, or adjacent systems experience.

Design and build Go-based storage control-plane services, CSI drivers, integrations, and tooling for Kubernetes AI and compute workloads. Automate storage provisioning using Terraform/OpenTofu and GitOps tools, support hybrid and bare-metal deployments, and develop observability for performance and reliability. Integrate enterprise storage platforms such as Dell PowerScale and VAST across cloud, edge, and air-gapped environments, including K0rdent, Cluster API, Harbor, and PKI/TLS infrastructure.

Provides department-wide technical direction for k0rdent across Kubernetes, AI infrastructure, AI applications, and observability. Designs cross-cutting systems, establishes engineering standards, resolves architectural risks, mentors Staff and Principal engineers, and aligns product strategy with durable technical execution. The role also engages customers, partners, upstream communities, and industry forums while contributing code and prototypes to solve complex infrastructure problems.

Design and implement infrastructure services for a GPU-as-a-Service platform. Build REST and gRPC APIs, bare-metal provisioning workflows, Kubernetes cluster automation, reconciliation loops, and durable asynchronous operations. Manage server enrollment, inspection, OS provisioning, cluster creation, hardware inventory interfaces, error handling, idempotency, and multi-tenant infrastructure reliability.

Own the vision, roadmap, backlog, and priorities for k0rdent AI observability across GPU infrastructure and distributed AI workloads. Define integrations for metrics, tracing, logs, telemetry, and alerting across Kubernetes, networking, storage, schedulers, inference platforms, and databases. Partner with engineering, marketing, field teams, customers, and ecosystem vendors to shape requirements, evaluate trade-offs, develop positioning, and support deployments.

Deploys, integrates, operates, and tunes high-performance NFS storage for Kubernetes, GPU, and AI workloads. Responsibilities include CSI integration, Linux and network optimization, storage lifecycle management, air-gapped platform support, infrastructure-as-code, GitOps automation, observability, and troubleshooting distributed storage performance and reliability across hybrid, edge, and bare-metal environments.