Senior AI Architect - AI Innovation & Discovery

Responsibilities

• AI Research & Technology Discovery
• Conduct applied research into emerging Artificial Intelligence technologies, Agentic AI frameworks, foundation models, developer tooling, and enterprise AI platforms to identify opportunities relevant to business and engineering teams.
• Continuously monitor industry trends, academic research, technology ecosystems, and market developments to assess their potential impact on enterprise AI adoption.
• Evaluate emerging technologies and innovation opportunities through structured analysis, comparative assessments, and evidence-based recommendations.
• Develop research papers, technical briefs, technology assessments, architecture recommendations, and innovation reports that support strategic decision-making.
• Act as a trusted advisor on AI trends, helping stakeholders understand emerging capabilities, limitations, risks, and opportunities.
• Innovation Strategy & Product Discovery
• Partner closely with Product Owners, Product Managers, Architects, and Engineering teams to identify innovation opportunities and define future platform capabilities.
• Support product discovery activities through market research, technology assessments, competitor analysis, and user-centric innovation studies.
• Translate business challenges into research initiatives and technology investigations that guide product strategy and investment decisions.
• Influence platform roadmaps by providing recommendations based on technical feasibility, market maturity, business value, and organizational priorities.
• Assist stakeholders in identifying emerging use cases and opportunities for AI-enabled transformation.
• Agentic AI & Emerging Technology Research
• Research Agentic AI architectures, multi-agent systems, orchestration frameworks, reasoning approaches, memory strategies, and autonomous workflow patterns.
• Evaluate evolving ecosystems around Large Language Models, enterprise AI platforms, AI governance, developer tooling, and AI-native development practices.
• Investigate new approaches to enterprise AI adoption and identify opportunities for reusable patterns, frameworks, and accelerators.
• Develop reference architectures, best practices, and technical guidance to support engineering teams.
• Proof-of-Concept Support
• Collaborate with engineering teams to validate research findings through lightweight experiments, prototypes, and proof-of-concepts.
• Support the early stages of innovation initiatives by helping define hypotheses, evaluation criteria, success measures, and experimentation approaches.
• Assist in translating research outcomes into actionable recommendations for future platform investments and product capabilities.
• Work closely with AI Engineers and Solution Architects to ensure research findings can be effectively operationalized.
• Knowledge Leadership & Community Engagement
• Establish and maintain a structured knowledge base of emerging AI technologies, research findings, industry trends, and innovation opportunities.
• Present research outcomes and recommendations to technical and business stakeholders.
• Facilitate innovation workshops, technology reviews, and knowledge-sharing sessions across the organization.
• Promote a culture of experimentation, learning, and evidence-based decision-making.
• What You Bring

Requirements

• Master's degree or PhD in Artificial Intelligence, Computer Science, Machine Learning, Data Science, Software Engineering, or a related field.
• Strong academic, research, or industry background in emerging technologies and innovation.
• Experience conducting applied research, technology assessments, or innovation-focused initiatives within enterprise environments.
• Functional Expertise
• Strong analytical and problem-solving skills with the ability to evaluate complex technical topics and communicate findings clearly.
• Experience translating research outcomes into practical recommendations and strategic guidance.
• Ability to balance academic rigor with business relevance and organizational priorities.
• Strong stakeholder engagement skills and the ability to influence decisions through data-driven insights and evidence-based recommendations.
• Excellent written and verbal communication skills, including experience producing executive-level reports and technical documentation.
• Technical Expertise
• Deep understanding of Generative AI, Agentic AI, Large Language Models, RAG architectures, AI orchestration frameworks, and enterprise AI ecosystems.
• Experience researching emerging AI technologies and evaluating their applicability to enterprise use cases.
• Familiarity with agent frameworks, AI developer tooling, cloud AI services, and enterprise platform architectures.
• Ability to assess technology maturity, scalability, governance implications, and implementation considerations.
• Hands-on experience supporting experiments, proof-of-concepts, or prototype development is desirable.
• Familiarity with SAP AI Core, SAP AI

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Company Intel

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