Senior AI Business Process Engineer

About the Role

The team at Tiger Analytics values collaboration and innovation. As a Senior AI Business Process Engineer, you will be part of a dynamic environment that encourages out-of-the-box thinking and supports the development of cutting-edge solutions. Your expertise will directly contribute to the company's mission to generate business value from data for its clients.

Given the nature of this role, the ideal candidate will have a strong foundation in business process engineering, excellent technical skills, particularly in BPMN 2.0 and DMN modeling, and the ability to communicate complex ideas effectively to both technical and non-technical stakeholders.

What You Will Do

• Lead process discovery and redesign workshops to analyze the current state, uncover root causes, and define future-state processes optimized for AI enablement.
• Design, validate, and iterate executable BPMN 2.0 and DMN models that serve as the authoritative blueprint for implementation and system integration.
• Incorporate deterministic and probabilistic decision automation into your designs and integrate AI agents to enhance business outcomes.
• Provide regular reporting on progress, risks, and outcomes in an agile manner to leadership and stakeholders.
• Partner with business and technical teams to ensure redesigned processes integrate seamlessly with enterprise systems and data flows, always meeting compliance requirements.
• Collaborate with vendors and partners to manage multiple projects in parallel, ensuring deliverables meet enterprise standards and demanding timelines.
• Support and enable process ownership and governance across departments, ensuring adherence to standards, security, and PII controls.
• Use process mining and analytics tools to measure adoption, performance, and business value realization.
• Advocate for practical AI adoption by demonstrating how redesigned processes and AI agents can augment human decision-making.

What We Are Looking For

• Bachelor's degree in Business, Information Systems, or a related field.
• 5+ years of experience in process engineering, BPM, or process optimization.
• Deep expertise in BPMN 2.0 and DMN modeling and process redesign.
• Strong skills in stakeholder facilitation, backlog management, and progress reporting.
• Experience supporting multiple concurrent projects with internal teams and external vendors.
• Hands-on experience designing and deploying BPMN/DMN directly in Camunda 8 (Zeebe), serving as the source of truth for delivery.
• Working knowledge of data modeling principles and the ability to collaborate effectively with data engineers and analysts.

Nice to Have

• Experience with process mining and analytics tools, such as Camunda Optimize.
• Certification in BPMN 2.0 or a related field.
• Knowledge of cloud-based process automation platforms.
• Experience in a consulting environment, working with various clients and projects.

Benefits and Perks

• The opportunity to work on cutting-edge projects that combine business process optimization with AI and data science.
• Collaborative and dynamic work environment that values innovation and creativity.
• Professional development opportunities, including training and certification programs.
• Flexible working conditions, including remote work options.
• Access to the latest tools and technologies in process automation and AI.
• Competitive compensation package.
• Health insurance and other benefits.
• Paid time off and holidays.

• Ensure your portfolio includes examples of process redesign and automation projects, highlighting your role in each.
• Develop a strong understanding of BPMN 2.0 and DMN, as well as experience with process mining and analytics tools.
• Practice articulating complex technical concepts in simple terms, as this will be crucial for stakeholder management.
• Be prepared to discuss how you have driven change and implemented process improvements in previous roles.
• Consider obtaining certifications in BPM or related fields to enhance your application.
• Prepare examples of times when you had to collaborate with multiple stakeholders, including technical teams, to drive a project forward.