3 days ago
Responsibilities
- Build trusted relationships and executive credibility with R&D leaders and scientific stakeholders.
- Lead R&D opportunities from pre-sales through delivery, including technical scoping, readiness assessment, feasibility, business value definition, staffing, estimates, success criteria, and phased planning.
- Partner with account, advisory, customer success, product engineering, and services teams to align end-to-end delivery.
- Translate scientific and engineering challenges into backlogs, epics, workflows, objectives, metrics, and target-state AI architectures.
- Design and deliver MVPs, proof-of-concepts, integrations, simulations, agents, production solutions, and data pipelines.
- Own technical workstreams across qualification, discovery, design, implementation, build, and post-go-live optimization.
- Evaluate emerging AI capabilities and provide scientific and technical oversight for credible, feasible solutions.
- Create reusable reference architectures, delivery playbooks, technical assets, and patterns, and provide product feedback to Microsoft Discovery engineering and product teams.
Requirements
- Extensive experience in science, engineering, technology consulting, product management, data science, machine learning, AI, or a related field.
- Experience supporting pharmaceutical or life sciences R&D, including areas such as drug discovery, genomics, bioinformatics, computational biology, or clinical development.
- Understanding of scientific methodologies, experimentation, data-informed decision-making, and R&D processes.
- Experience applying AI, machine learning, generative AI, data science, simulation technologies, or advanced analytics to business or scientific scenarios.
- Ability to collaborate with technical specialists and business decision-makers and build alignment across teams.
- Strong communication, presentation, stakeholder engagement, problem-solving, and adaptability skills.
- Preferred: advanced degree or equivalent professional experience in Chemistry, Biology, Physics, Engineering, or a related discipline.
- Preferred: understanding of data science and machine learning concepts, including exploratory data analysis, model development, and model evaluation.
- Preferred: familiarity with Azure cloud services, AI agent architectures, knowledge graphs, containerized applications, and scientific computing environments.
- Preferred: experience with product planning, iterative delivery, prioritization, multidisciplinary collaboration, innovative initiatives, or AI-assisted development tools such as GitHub Copilot, Claude Code, or Codex.
Benefits
- The typical base pay range is £77,600.00–£132,500.00 per year in the United Kingdom.
- Certain roles may be eligible for benefits and other compensation.
- Applications are accepted on an ongoing basis until the position is filled, with the posting open for a minimum of five days.
Tech Stack
Categories
Solutions Engineering
About Microsoft
Every company has a mission. What's ours? To empower every person and every organization to achieve more. We believe technology can and should be a force for good and that meaningful innovation contributes to a brighter world in the future and today. Our culture doesn’t just encourage curiosity; it embraces it. Each day we make progress together by showing up as our authentic selves. We show up with a learn-it-all mentality. We show up cheering on others, knowing their success doesn't diminish our own. We show up every day open to learning our own biases, changing our behavior, and inviting in differences. Because impact matters. Microsoft operates in 190 countries and is made up of approximately 228,000 passionate employees worldwide.