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At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.
What you’ll do:
Enterprise software is shifting from passive process infrastructure to active decision infrastructure. SAP is pioneering autonomous enterprise decision systems that combine optimization science, quantum computing, and artificial intelligence to help organizations navigate complexity and execute under real-world constraints.
The Development Manager Optimization, Quantum & AI will lead the transformation of an established data science team into a strategic contributor to SAP’s autonomous decision infrastructure. You will manage a team with ten years of experience in classical analytics and guide their evolution toward building decision-capable systems that evaluate, optimize, orchestrate, and execute under dynamic constraints.
This role requires dual leadership: transforming team capabilities while leveraging deep domain expertise to accelerate impact. You will bridge classical data science with decision infrastructure—moving from descriptive analytics to prescriptive systems, from model building to architecture design, and from standalone insights to integrated execution platforms. As transformation progresses, the team’s scope will expand across SAP’s entire application portfolio, positioning them as the core engine of SAP’s Autonomous Enterprise with Quantum Brain.
The Role:
• Lead the technical transformation of an established data science team toward autonomous decision systems, building capability in optimization algorithms, constraint-based problem solving, and hybrid computational architectures.
• Integrate your team into the broader Optimization, Quantum & AI organization as strategic contributors to decision infrastructure, fostering collaboration with optimization engineers, quantum researchers, and AI architects.
• Develop team expertise in quantum computing concepts and identify opportunities where quantum-enhanced solutions create enterprise value.
• Build understanding of orchestration systems, execution layers, and enterprise integration requirements—positioning the team within agent layers, optimization solvers, and operational platforms.
• Maintain productivity during transformation, delivering measurable improvement in decision quality, planning speed, or operational performance while building new capabilities.
• Assess individual readiness, create personalized development plans, and manage performance honestly—recognizing growth, supporting struggles, and making difficult decisions about team composition.
• Collaborate with architects and product managers to translate business requirements from diverse domains—supply chain, finance, HR, procurement, customer operations—into decision architecture challenges, positioning the team to become the core engine for SAP’s Autonomous Enterprise with Quantum Brain across the entire application portfolio.
What you bring:
• Leadership experience in software development with proven track record leading teams through significant capability shifts or technology transitions (5+ years).
• Well-honed people management skills with demonstrated success in upskilling teams, introducing new methodologies, and delivering results during organizational change.
• Technical credibility in data science, optimization, or systems engineering sufficient to earn respect from practitioners and engage in architectural discussions.
• Experience integrating teams into broader technical organizations and breaking down silos between specialized functions.
• Understanding of how software systems operate in complex enterprise environments across multiple business domains.
• Ability to work in a multi-domain environment, crossing technical, academic, research, and business boundaries—with vision to expand team scope across SAP’s entire application portfolio.
• Excellent communication, negotiation, and presentation skills with ability to translate vision into concrete action.
• Highly professional and structured working style with capacity to manage complex stakeholder networks.
• Ability to thrive in dynamic environments that cross organizational boundaries while maintaining delivery accountability.
• Degree in Computer Science, Mathematics, Physics, or related field; strong willingness to immerse oneself in optimization, quantum computing, and decision architecture is essential.
Meet your team:
You’ll join SAP’s Optimization, Quantum & AI organization—a team redefining what enterprise systems can do. We’re architecting decision-capable infrastructure where optimization science, quantum computing, and artificial intelligence converge into deployable systems. This team will become the core engine of SAP’s Autonomous Enterprise with Quantum Brain, expanding across the entire application portfolio. We operate with clarity about what matters: decision quality, system reliability, deployment credibility, and governance. If you want to lead teams through genuine transformation where constraints are real and strategic impact is organization-wide—this is your opportunity.
Bring out your best
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.
We win with inclusion
SAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.
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Requisition ID: 453522 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Management | Employment Type: Regular Full Time or Part-Time | Additional Locations: #LI-Hybrid
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The structural evolution of enterprise software toward autonomous decision infrastructure necessitates a specialized tier of leadership capable of orchestrating the convergence of classical optimization, artificial intelligence, and emerging quantum methodologies. As global commerce faces increasing volatility, the transition from passive process record-keeping to active, prescriptive execution layers serves as a critical determinant for industrial resilience and competitive positioning. This role type addresses the fundamental integration challenge of translating deep-tech breakthroughs into scalable, multi-domain application logic that operates under real-world constraints. Market signals, including the rise of hybrid classical-quantum cloud architectures and the expansion of agentic AI frameworks, indicate that the ability to transform established data science units into strategic decision-engine contributors is now a primary bottleneck in the digital value chain. By bridging the gap between theoretical algorithmic research and high-fidelity enterprise production, this function ensures that organizational roadmaps remain aligned with the rapid maturation of high-performance computational hardware.
The quantum computing and optimization ecosystem is currently entering a phase of industrialization characterized by the integration of specialized solvers into existing enterprise resource planning (ERP) and supply chain management (SCM) environments. While initial market focus centered on hardware benchmarks and laboratory prototypes, the current value-chain emphasis has shifted toward the "application enablement" layer. Within this layer, the primary objective is to develop interoperable middleware and orchestration systems that can offload complex combinatorial subtasks to the most efficient available processor, whether classical, GPU-accelerated, or quantum-centric. This hybrid architecture is essential for addressing intractable problems in logistics, financial risk modeling, and materials science that exceed the capabilities of traditional deterministic systems.
Macro-level analysis reveals that a significant structural gap exists between academic algorithmic innovation and the operational requirements of global software ecosystems. Many organizations possess deep expertise in descriptive and predictive analytics but lack the architectural frameworks to move into autonomous prescriptive systems. Addressing this Technology Readiness Level (TRL) mismatch requires a strategic pivot from model-centric development to system-centric orchestration. Furthermore, the fragmentation of the quantum vendor landscape necessitates the creation of hardware-agnostic software stacks that protect capital-intensive enterprise investments from premature technology lock-in.
Current industry focus lies on bridging classical and quantum capabilities at scale through the development of specialized talent pipelines and cross-functional centers of expertise. These centers are tasked with navigating the complexities of dynamic constraint satisfaction and multi-objective optimization across diverse business lines. As global entities like SAP pioneer these autonomous systems, the success of the ecosystem depends on leadership that can harmonize the deterministic nature of enterprise software with the probabilistic advantages of quantum-enhanced intelligence. This transition is not merely a technical upgrade but a fundamental redesign of how organizations evaluate, optimize, and execute strategic decisions in real-time.
The capability architecture for this role type centers on the structural alignment of advanced mathematical optimization with modern software engineering principles and hybrid computational logic. At the foundational level, mastery of algorithmic translation—specifically the ability to reformulate complex business constraints into solver-compatible objective functions—is essential for ensuring the stability and reproducibility of autonomous decisions. This technical proficiency must be coupled with a deep understanding of enterprise integration patterns, where optimization kernels are embedded within larger agentic workflows to facilitate seamless execution across diverse application portfolios. These capabilities are vital for the architectural throughput of deep-tech initiatives, as they directly influence the scalability and deployment credibility of systems in high-stakes domains such as global procurement, human capital management, and customer operations. Beyond individual execution, this role type facilitates the high-level coupling of data science research with industrial-grade software lifecycles, ensuring that emerging techniques in quantum machine learning and constraint programming are grounded in realistic infrastructure trajectories and governance standards.
Accelerates the deterministic maturation of autonomous decision systems for global enterprise application portfolios
Mitigates systemic integration risks by establishing robust architectural frameworks for hybrid classical-quantum computational workflows
Facilitates the transition from descriptive data science to prescriptive, autonomous execution engines across the value chain
Reduces iteration friction in complex supply chain and logistics optimization through the deployment of advanced solver technologies
Strengthens industrial competitiveness by securing early-mover advantages in the emerging quantum-enhanced decision economy
Harmonizes abstract research breakthroughs with the practical reliability requirements of high-volume enterprise production environments
Optimizes the lifecycle of enterprise software by transforming passive record systems into active decision-capable infrastructure
Supports the scaling of quantum adoption by identifying and validating high-impact use cases across diverse business domains
Shortens time-to-value for deep-tech investments through the strategic upskilling of established technical workforces
Improves the reliability of multi-stakeholder optimization projects by implementing standardized benchmarking and architectural best practices
Protects long-term technology investments by developing modular, hardware-agnostic software toolchains and orchestration layers
Enables the strategic orchestration of development efforts across global networks of internal researchers and external technology partners
Industry Tags: Autonomous Enterprise, Quantum Optimization, Hybrid Quantum-Classical Computing, Decision Intelligence, Enterprise Software Architecture, Technology Readiness Level, Algorithmic Research, Supply Chain Optimization, AI Governance
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