Industry Architect - Research & Development

Microsoft•,

9d•$101,800 - $207,600

About The Position

Microsoft is helping define a new era of scientific and industrial innovation: one where agentic AI, cloud-scale computing, data, simulation, and human expertise come together to accelerate breakthroughs that once took months or years. As customers look to transform how they discover new materials, medicines, products, processes, and research insights, they need more than a platform — they need deeply technical partners who can turn ambition into working solutions. This role has three distinct dimensions: shaping customer outcomes, leading technical delivery, and scaling R&D (Research & Development) motions. We are seeking an Industry Architect - Research & Development with the mindset, executive presence, and leadership ability to shape complex R&D opportunities. You will work directly with R&D leaders, scientific researchers, account teams, industry leaders, and Microsoft product engineering to identify high-value R&D scenarios. The Industry Architect serves as the strategic bridge between scientific innovation, business outcomes, and Microsoft’s AI technologies, shaping high-value opportunities from pre-sales through delivery and leading first-of-its-kind MVPs and cutting-edge production deployments. This is a role for builders who thrive in ambiguity, move comfortably from high level customer needs to whiteboard to code, and are energized by solving complex customer problems in the real world. You will help customers reimagine R&D workflows through Microsoft AI while also shaping the repeatable patterns, product feedback, and delivery motions that scale this frontier AI business across industries. If you are excited by the opportunity to co-engineer with customers, unlock new scientific and industrial possibilities, and help establish one of Microsoft’s most strategic AI growth motions, this role is for you.

Requirements

Master's Degree in Computer Science, Information Technology, Engineering, or related field AND 4+ years experience in science, engineering, technology consulting, product management, data science, machine learning, AI, or a related field OR Bachelor's Degree in Computer Science, Information Technology, Engineering, or related field AND 6+ years experience in science, engineering, technology consulting, product management, data science, machine learning, AI, or a related field OR equivalent experience.

Nice To Haves

Direct experience in pharma or life sciences R&D, including drug discovery, target identification, lead optimization, preclinical research, translational medicine, clinical development, biotechnology, genomics, bioinformatics, computational biology, regulatory science, or real-world evidence.
Understanding of scientific methods, experimentation, data-driven decision making, and R&D workflows.
Experience applying AI, machine learning, generative AI, data science, simulation, or advanced analytics to real-world business or scientific problems.
Proven ability to work effectively with both highly technical experts and executive business stakeholders.
Exceptional communication, storytelling, and stakeholder-management skills.
Demonstrated ability to influence without authority and drive cross-organizational outcomes.
Problem-solving skills in ambiguous, fast-moving environments.
Understanding of data science and machine learning (algorithms, exploratory data analysis, model development, and evaluation)
Familiarity with Microsoft Azure cloud services (e.g., Foundry and AI Search), agentic AI architectures, knowledge graphs, microservices/containers, and scientific high-performance computing.
Experience with product management, agile delivery, and backlog management.
Experience working across large matrixed organizations and collaborating with engineering, research, product, and sales teams.
History of leading first-of-a-kind initiatives and innovation-focused programs.
Experience using Github Copilot, Claude Code, Codex, or similar.

Responsibilities

Build strong executive presence and credibility with R&D leaders, with the mindset to drive strategic, first-of-its-kind R&D engagements.
Lead R&D opportunities from pre-sales through delivery, including technical scoping, use case qualification, customer readiness, data and compute assessment, solution feasibility, business value definition, staffing models, success criteria, effort estimates, and phased delivery plans.
Partner with account teams, Industry Advisors, Customer Success, Product Engineering, and Services teams to shape R&D engagements from early opportunity through implementation, drive cross-functional alignment across Microsoft.
Bridge business objectives, scientific requirements, and technical implementation teams to ensure successful end-to-end solution delivery. Work side-by-side with customer scientists, researchers, computational teams, engineers, executives, and UX researchers to articulate specific R&D outcomes and roadmaps, align technical delivery with business outcomes, and establish trusted advisor relationships.
Translate customer R&D, scientific, engineering, or advanced computing challenges into product backlogs, epics, user stories, tasks, research objectives, success metrics, scientific workflows, and target-state AI architectures on Microsoft Discovery and Azure.
Lead design and delivery of MVPs, proof-of-concepts, and production-ready solutions across Discovery workflows, agents, integrations, simulations, and data pipelines.
Own technical workstreams across the engagement lifecycle: qualification and planning, discovery and design, implementation and build, and post-go-live optimization
Evaluate emerging AI capabilities and provide scientific and technical oversight throughout the engagement, ensuring solutions are scientifically credible, technically feasible, aligned to customer goals, and applicable to scientific and engineering workflows.
Develop reusable patterns, reference architectures, delivery playbooks, technical assets, and best practices that help scale R&D patterns across customers, industries, and regions. Capture product feedback and field learnings to influence the Microsoft Discovery roadmap, engineering priorities, and repeatable industry motions.