Top Tech Jobs & Startup Jobs in Boston, MA

Lead design and implementation of a production-grade LLM inference platform: deploy and serve models on GPU infrastructure, optimize latency and cost with quantization/batching/caching/routing, build infrastructure in Python or Golang, operate serving frameworks (vLLM, SGLang, TensorRT-LLM), and own the inference roadmap working with CTO and Product.

Own and execute a high-velocity social program for LinkedIn and X: plan and publish content, translate executive technical insights into thought leadership, manage community engagement, react to industry news, and provide live event coverage while upholding editorial quality and brand voice.

Lead product direction for cloud-native GPU infrastructure and Kubernetes virtualization. Translate business priorities into technical specs, run alpha/beta validations, engage platform-engineer customers, define market positioning, and align engineering, sales, and marketing to ship and support scalable multi-tenant GPU platforms.

Lead end-to-end application and product security for a Kubernetes-based multi-tenant platform. Perform deep security reviews of Go services, Kubernetes controllers, and frontends; lead threat modeling; integrate automated security checks into CI; manage vulnerability lifecycle; develop security-related features; and train developers on secure coding and attack vectors.

Lead product direction for vMetal, defining specs and tradeoffs, validating alpha/beta builds on bare metal, engaging platform-engineer customers, positioning the product in the GPU/bare-metal ecosystem, and aligning engineering, sales, and GTM teams.

Lead contract negotiation and review for enterprise customers and vendors, manage high-volume deals, build templates and playbooks, partner with sales, and provide fast commercial legal advice using tooling and outside counsel when needed.

Design and launch the company’s first go-to-market enablement function: learning paths, certifications, onboarding cohorts, and ongoing technical and sales enablement. Partner with engineering, product, and marketing to convert technical content into repeatable programs, shorten new-hire ramp, measure enablement impact, and enable sellers, SDRs, and field engineers to sell to platform and DevOps audiences.

Lead architecture and execution of vNode runtime integration with containerd and the kubelet, define and test namespace-based isolation primitives, mentor engineers, run design reviews, operate internal tenant clusters, and represent the project in upstream communities and conferences.

Lead architecture and backend development for the vCluster platform by designing and implementing Kubernetes-native solutions in Go, owning features end-to-end, contributing to open-source, and solving deep systems challenges around multi-tenancy, isolation, and GPU infrastructure.

Lead end-to-end GPU-focused Kubernetes deployments from bare metal to production-ready vCluster environments. Configure and troubleshoot GPU nodes (GPU Operator, CUDA, RDMA/InfiniBand), CNI and storage (CSI, Ceph/Rook/Weka/Longhorn), validate managed K8s, produce playbooks, transfer knowledge to customers, and feed infrastructure learnings back to Product and Engineering while supporting pre-sales proofs of value.