Jobs at Beamery

Manage Beamery’s internal IT strategy, infrastructure, security, compliance, systems, devices, software, and end-user support. Own the IT roadmap, budget, KPIs, disaster recovery, asset lifecycle, vendor contracts, employee onboarding and offboarding, and automation initiatives. The role requires strong expertise in endpoint management, cloud platforms, networking, ITSM, troubleshooting, and ISO 27001, SOC 2, and GDPR frameworks. It is an individual contributor position requiring five days onsite weekly in London.

Manage Beamery’s global internal IT infrastructure, systems, devices, cloud resources, software stack, vendors, and employee technology lifecycle. Develop IT strategy, budgets, KPIs, disaster recovery, and compliance support for ISO 27001 and SOC 2. Provide hands-on end-user support, improve operational efficiency through automation, manage hardware and software assets, and ensure secure onboarding and offboarding. The role requires a strong onsite presence five days per week in London.

Sell Beamerys enterprise talent and skills platform to mid-size and large accounts. Prospect and qualify target accounts, lead executive conversations, negotiate and close new business, collaborate cross-functionally to craft value propositions, represent customer feedback internally, and coach junior sellers.

Lead platform architecture, reliability, and infrastructure initiatives; design scalable cloud services; mentor engineers; own platform standards, incident response, observability, cost controls; stay hands-on via on-call and partner with product and cross-functional teams.

Own the Data Foundry product strategy and roadmap, balancing infrastructure and commercial data-as-a-service. Partner with CRM and Workforce Suite PMs, data science, and engineering to define data contracts, prioritize delivery, ensure governance/security, and drive adoption and GTM for MCP/API channels. Measure success via usage, value, and commercial metrics.

Build and maintain product reporting and dashboards, partner with product managers to analyze usage, adoption and retention, maintain product analytics stack (Pendo, Hex), enable PM self-serve, design and instrument LLM/AI agent workflows and automation, evaluate emerging AI tooling and document reproducible agent architectures.

Review and improve AI-generated role profiles for accuracy and consistency; spot and fix data issues; run QA workflows using agentic tools (e.g., Claude); collaborate with Data Science and Professional Services to define QA metrics, log defects, validate pipeline fixes, and document QA processes and standards.

Lead the data platform's technical strategy and architecture, design analytics/semantic/AI data layers, set modelling and reliability standards, drive observability and data quality, mentor senior engineers, and coordinate cross-team modernization and incident response.