Senior AI Architect - AI Innovation & Discovery

What You'll Do 

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 

Qualifications 

• 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 Launchpad, SAP BTP, or similar enterprise AI platforms is advantageous. 

Leadership & Collaboration 

• Demonstrated ability to influence technical and strategic decisions through research and thought leadership. 
• Strong collaboration skills across product, engineering, architecture, and business functions. 
• Passion for continuous learning, innovation, and emerging technologies. 
• Recognized for curiosity, critical thinking, intellectual rigor, and the ability to challenge assumptions constructively. 

Success Profile 

The ideal candidate combines the curiosity of a researcher, the mindset of an innovator, and the pragmatism of a technology strategist. They are passionate about exploring emerging AI technologies, translating research into actionable recommendations, and influencing the future direction of enterprise AI platforms. They excel at connecting technology possibilities with business opportunities and enabling informed investment decisions through evidence-based insights.