Solution Sales Advisor - Microsoft Frontier Company
Build trusted relationships with customer business and technical executives, gain sponsorship for priority outcomes, and lead strategic Cloud and AI opportunities from qualification and origination through commercial commitment, execution readiness, transition and early value realisation.
Own the end-to-end technical strategy across cloud foundations, applications, data, databases, security and AI. Shape architectures for enterprise IQ, agentic systems and scaled AI adoption, with governance, Responsible AI, sovereignty, resiliency, observability, capacity and operational readiness designed in from the outset.
Identify priority business processes that can be reimagined through collaboration between people and agents, and decide when a more extensive Forward Deployed Engineering engagement is needed. Co-design production solutions with Engineering Studios, industry specialists, delivery teams and partners, making sure customer capability, ownership, operating model and continuous improvement are built into the engagement.
Develop the customer value case, technical narrative, transformation roadmap and consumption plan. Make sure each plan is clear, realistic and optimised; connects workloads, capacity, services, investments and milestones to measurable outcomes; and supports a sound commercial approach, forecast and path from commitment to consumption.
Bring together the Strategic Partnership Lead, account team, specialist and success organisations, Engineering Studios, Industry Advisory, delivery teams, partners, finance, deal desk and product engineering around one outcome-led plan. Set clear ownership, quality checkpoints, workback plans and decision cadences, then lead a structured handover that keeps customer context, delivery accountability and consumption progress intact.
Experience leading consultative technical pursuits and enterprise transformation programmes from qualification and strategy through architecture, commercial commitment, execution planning and transition.
Ability to translate customer priorities and emerging technology into a measurable value case, a clear and optimised consumption plan, realistic growth and adoption forecasts, and a commercial approach that aligns workloads, services, capacity, investments and milestones.
Sound judgement, structured problem-solving and executive communication, with the ability to bring clarity to ambiguous situations, set decision and delivery cadences, manage risks and dependencies, and follow through across a distributed virtual team.
Understanding of enterprise and public-sector transformation, industry value chains, product and platform business models, and the organisational change needed to move AI from experimentation into scaled operations.
Experience in enterprise AI transformation, including data foundations, machine learning, foundation models, agentic systems, AI application development, evaluation, observability, governance, security, Responsible AI and redesigning priority business processes for collaboration between people and agents.
Experience shaping resilient, secure and cost-effective cloud and AI platforms; modernising applications, data and operating practices; and planning capacity, sovereignty, reliability and delivery readiness for adoption at enterprise scale.
Understanding of cloud-native and hybrid architecture, Kubernetes, platform engineering, DevOps, infrastructure as code, reliability, observability, security, automation, capacity planning and operations at scale.
Experience applying FinOps, cloud economics, pricing and licensing, workload optimisation and investment planning to create sustainable strategic commitments, manage consumption risk and improve customer value realisation over the life of the partnership.
