• Gather client requirements, design optimized solutions • Deploy a new solution or augment an existing HPC/AI solution from the ground up • Consult on and assist with day-to-day management of clients’ research compute infrastructure environments • Maintain HPC/AI infrastructure in Linux-based environments for new and existing clients • Lead technical discussions and be the face to the client in preparation for and during engagements • Validate solution designs, meet client requirements, and ensure they are technically feasible and deployable • Ensure solutions are simple and easy to understand while taking into account the client’s overall capabilities / skills • Scope out and detail professional services deliverables setting clear client expectations • Build documentation and provide knowledge transfer required for clients to support their environments • Display expertise in storage, networking, data protection, digital archiving, and other infrastructure technologies. • Gain advanced expertise of and certifications from the vendors Cambridge uses in our solution stack.

• Design and develop AI governance and AIMS frameworks, including AI Governance standards and playbooks, aligned with organizational values and global norms. • Contribute to the design and implementation of AI Governance related tools. • Ensure PIAs, impact and risk assessments are timely and shared with Leadership to enable effective risk mitigation (e.g., EU AI ACT Risk Assessment, Data Protection Impact Assessment completion). • Maintaining classification and risk registers for AI use cases. • Contribute to the KPIs and adoption metrics, for the AI Governance standards across Nebius, unlocking innovation and business value through leveraging data and AI. • Gather, analyze and manage requirements, coming from various stakeholders (e.g., Cybersecurity, Privacy, Legal and respective Business Units).

• Own post-sale outcomes for a set of strategic enterprise accounts, with a focus on adoption, retention, and expansion. • Work hands-on with teams at some of the world’s largest enterprises to understand their workflows, development practices, and organizational constraints, and help adapt Builder to fit how they actually work. • Partner closely with Customer Engineers during technical onboarding and early implementation, then carry ownership forward as customers move into sustained usage and scale. • Guide customers through change management as they adopt AI-assisted and AI-powered workflows, helping build habits that stick rather than one-time successes. • Translate customer goals and constraints into clear success criteria, helping define what “good” looks like as automation and AI play a larger role in production workflows. • Connect product usage and customer behavior to real business outcomes, using those insights to drive retention, expansion, and deeper adoption across teams. • Serve as a trusted advisor to both technical and non-technical stakeholders, including engineers, product managers, designers, and executives. • Act as a strong voice of the customer internally, partnering with Product and Engineering to surface patterns, gaps, and opportunities to serve our customers.

• Manage the AI implementation projects; design, develop and implement innovative conversational AI solutions and automations in email, phone and chat contacts, ensuring a seamless and enhanced user experience across various channels, regions, languages and brands. • Successful implementation of conversational AI solutions in operations, increasing the servicing of requests using automated solutions and processes. • Containment: Number of successful automated/bot interactions vs. escalations (transfer to agent). • Accuracy in intent recognition and helpfulness of automated solutions. • Customer Satisfaction (CSAT). • Continuous improvement in conversational AI and channel automation performance metrics. • Design and develop conversational AI solutions and channel automations, such as AI agents, email intent recognition & classification and action triggering & routing; translating business requirements into customer-focused conversational solutions. • Manage the end-to-end development and implementation of conversational AI features, collaborating with different stakeholders; incl.giving support to internal teams for the operational readiness before implementation. • Communicate issues, ensure resolution, and define continuous developments and improvements, collaborating with Technology, Product and Data teams. • Identify opportunities and potential new use cases for additional AI applications, collaborating with different stakeholders. • Stay updated with the latest conversational AI trends and best practices.