Top Tech Jobs & Startup Jobs in Boston, MA

Owns end-to-end delivery of complex customer infrastructure builds lasting 90–120 days. Coordinates customers, OEMs, infrastructure partners, integrators, and internal teams; manages schedules, scope, risks, dependencies, budgets, change control, phased acceptance, and operational handoffs. Leads executive communications, resolves blockers, improves professional services methodologies, mentors engagement managers, and supports customer growth opportunities.

Deliver enterprise solutions and services for WEKA customers, leading product onboarding, installation, deployment, and production implementation. Manage deployment projects, assess risks, document solution architectures, develop automation and custom scripts, test deployments, and troubleshoot AI/HPC infrastructure in Linux and cloud or on-premises environments. Collaborate with sales, engineering, product, customers, and partners while providing technical guidance, knowledge transfer, and customer support.

Serves as a top-tier networking escalation expert for WEKA deployments across HPC, AI/ML, enterprise, cloud, and hybrid environments. Troubleshoots complex Layer 1–4 issues, leads root-cause analysis, supports high-severity incidents, mentors technical teams, improves diagnostic tooling, develops technical documentation, and influences product networking design. Requires deep expertise in Ethernet, InfiniBand, RDMA, Linux networking, distributed systems, and large-scale datacenter fabrics, along with 24/7 on-call support and occasional travel.

Provides senior technical support for enterprise infrastructure customers, diagnosing hardware, networking, storage, cloud, and distributed-system issues. Serves as the liaison between customers, account teams, partners, and Engineering; monitors systems, manages support cases, documents solutions, improves product supportability, and contributes to customer-facing knowledge resources. Requires on-call availability, flexible work hours, and potential regional or international travel.

Own product marketing for WEKA’s AI inference business, defining positioning, messaging, use cases, competitive differentiation, and economic value. Partner with Product, Engineering, Sales, customers, and cloud providers to validate market opportunities, recruit design partners, create proof and content, launch capabilities, and build repeatable sales enablement. The role requires deep understanding of AI infrastructure and inference economics, strong storytelling, and hands-on execution in an evolving early-stage market.

Own WEKA’s OEM alliance portfolio across North America, managing strategic relationships with partners including Dell, AMD, HPE, Cisco, Hitachi, Lenovo, and Supermicro. Develop joint go-to-market strategies, enable partner sales teams, build executive alignment, generate pipeline, support co-selling, and represent WEKA at industry events. The role focuses on positioning WEKA’s AI infrastructure and storage platform across partner ecosystems while creating integrated customer opportunities.

Own WEKA’s North American ISV alliance portfolio across the AI/ML ecosystem. Develop joint go-to-market strategies, integrations, enablement programs, executive relationships, co-selling motions, and pipeline opportunities. Position WEKA as the data platform for AI software stacks while coordinating with product, engineering, sales, marketing, OEM, cloud, and technology partners to deliver validated solutions and revenue growth.

Manage WEKA’s North American ISV alliance portfolio across AI/ML, cloud, data, and Kubernetes ecosystems. Develop joint go-to-market strategies, drive co-selling and pipeline, secure executive alignment, and create revenue opportunities. Coordinate technical integrations, certifications, marketplace listings, and reference architectures with product and engineering teams. Deliver partner enablement, identify cross-partner solutions, and represent WEKA at industry events and executive briefings.

The Senior Product Manager will define and manage the roadmap for WEKA appliances, liaise with ecosystem partners, and ensure product delivery while maintaining market insights and collaboration with sales and engineering teams.

Own the AMG product roadmap for NeuralMesh: define KV-cache/prefix-cache offload, memory tiering, and integrations with inference engines and orchestration. Translate GPU/memory/network tradeoffs into product requirements, validate benchmarks with enterprise customers and GPU-cloud partners, partner with NVIDIA for certifications, and support sales with technical positioning to reduce cost-per-token and improve inference SLAs at scale.