1 day ago
Remote, United Kingdom +3 moreStaff+
Responsibilities
- Build executive credibility with R&D leaders and drive strategic, first-of-its-kind R&D engagements.
- Lead opportunities from pre-sales through delivery, including technical scoping, use-case qualification, readiness assessment, feasibility, business-value definition, staffing, estimates, success criteria, and phased plans.
- Coordinate account, advisory, customer success, product engineering, and services teams to deliver end-to-end solutions.
- Work with customer scientists, researchers, engineers, executives, and UX researchers to define R&D outcomes, workflows, roadmaps, and architectures.
- Translate scientific and engineering challenges into backlogs, epics, user stories, research objectives, metrics, and target-state AI architectures.
- Lead MVPs, proofs of concept, integrations, simulations, agents, data pipelines, and production-ready deployments.
- Own technical workstreams across qualification, planning, discovery, design, implementation, build, and post-go-live optimization.
- Evaluate emerging AI capabilities and ensure solutions are scientifically credible, technically feasible, and aligned with customer goals.
- Create reusable reference architectures, delivery playbooks, technical assets, and industry patterns while influencing Microsoft Discovery product priorities.
Requirements
- Extensive professional experience in science, engineering, technology consulting, product management, data science, machine learning, AI, or a related field.
- Direct experience in materials science or industrial R&D, including areas such as chemistry, polymers, advanced materials, formulation science, computational materials, specialty chemicals, manufacturing R&D, or energy materials.
- Understanding of scientific methods, experimentation, data-informed decision-making, and R&D workflows.
- Experience applying AI, machine learning, generative AI, data science, simulation, or advanced analytics to scientific or business challenges.
- Ability to collaborate with technical specialists and business stakeholders, communicate effectively, influence across teams, and drive organizational outcomes.
- Preferred: PhD, MS, or equivalent experience in Chemistry, Biology, Physics, Engineering, or a related discipline.
- Preferred: understanding of data science and machine learning algorithms, exploratory data analysis, model development, and model evaluation.
- Preferred: familiarity with Azure services such as Foundry and AI Search, agentic AI architectures, knowledge graphs, microservices, containers, and scientific high-performance computing.
- Preferred: product management, Agile delivery, backlog management, large-organization collaboration, innovative solution development, and tools such as GitHub Copilot, Claude Code, or Codex.
Benefits
- Base pay ranges are listed by location: Germany €117,400–€252,500 per year; United Kingdom £89,300–£200,500 per year; Ireland €101,100–€213,700 per year; Netherlands €113,800–€265,600 per year; and Portugal €81,700–€223,900 per year.
- Certain roles may be eligible for benefits and other compensation.
- The position is open for a minimum of five days, with applications accepted on an ongoing basis until filled.
Tech Stack
Categories
Solutions Engineering
About Microsoft
Microsoft develops operating systems, productivity software, cloud services, developer tools, and consumer devices for individuals, enterprises, and governments. Its main products include Windows, Microsoft 365, Azure, Visual Studio/GitHub, Xbox, and LinkedIn; revenue comes from software subscriptions and licenses, cloud consumption, hardware sales, and advertising. Founded in 1975 and headquartered in Redmond, Washington, Microsoft is a public company traded on Nasdaq.