Director of Software Engineering - Workplace Technology at JPMorgan Chase

Join us to shape the future of AI by bridging the physical and digital worlds. You will lead a talented team focused on pioneering phygital AI solutions, leveraging IoT and edge-to-cloud computing. We offer an environment where your vision and leadership can drive impactful change. Your expertise will empower our team to deliver scalable, real-time AI innovations. Experience career growth and make a difference in a collaborative, forward-thinking culture.

• As a Director of Software Engineering
• Phygital AI Research & Development at JPMorgan Chase in our innovative Phygital AI R&D Center, you will guide a group of engineers in developing cutting-edge AI solutions that integrate IoT and edge-to-cloud architectures. You will mentor and inspire your team to excel in data interoperability, real-time processing, and scalable analytics. Your role will be pivotal in ensuring seamless convergence between physical and digital systems. You will foster a culture of collaboration, creativity, and continuous learning. Together, we will overcome technical challenges and deliver impactful phygital AI advancements.

Job Responsibilities:

• Develops strategic roadmaps for phygital AI leveraging IoT sensors, edge computing, and cloud infrastructure
• Mentors and upskill engineers in IoT data interoperability, edge-to-cloud workflows, and AI model deployment
• Implements governance for IoT-generated data streams, applying FAIR principles for findability and reusability
• Addresses cybersecurity and scalability challenges across edge devices and cloud platforms
• Drives R&D from IoT pilots to production-scale phygital solutions, ensuring interoperability and advanced analytics integration
• Architects resilient edge-to-cloud pipelines supporting phygital innovation
• Fosters a collaborative and inclusive team environment focused on continuous learning
• Translates IoT and edge-cloud complexities into business value for cross-functional teams
• Champions innovation and overcome barriers to scaling IoT deployments
• Ensures data lifecycle management from generation to cloud-based analysis
• Leads efforts to integrate AI/ML with IoT ecosystems for real-time and scalable analytics

Required Qualifications, Capabilities, and Skills:

• Formal training or certification on AI/IoT R&D concepts and expert applied experience. In addition, advanced experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise

• Experienced leading teams in edge-to-cloud deployments for phygital or Industry 4.0 applications.

• Leadership & People Management

• Transformational leadership with experience upskilling teams in emerging technologies like IoT and edge computing.

• Proven track record in deploying IoT solutions for operations optimization, predictive maintenance, and real-time monitoring, including sensor integration and data interoperability across fragmented stacks.

• Edge-to-Cloud Compute Proficiency: Deep hands-on knowledge of edge computing for low-latency AI inference (e.g., 5G-enabled processing) transitioning to cloud platforms for advanced ML, big data analytics, and scalable storage.

• AI technical depth in integrating IoT data with phygital models, including prompt engineering for GenAI on edge devices and cloud-based validation.

• Expertise in FAIR data principles for IoT ecosystems, enabling integration with AI/ML, cloud computing, and edge workflows.

• Ability to architect resilient edge-to-cloud pipelines that support phygital R&D, addressing challenges like cybersecurity, cost, and talent gaps.

• Effective stakeholder communication translating IoT/edge-cloud complexities into business value for cross-functional teams.

Preferred Qualifications, Capabilities, and Skills:

• Advanced degree in Computer Science, AI, or related field
• Certifications in cloud platforms such as AWS Io

T or Azure Edge: