Be the one building AI-powered experiences where they matter most.
At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.
Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day.
Job Description
Job Title: Senior Business Systems Analyst
Remote / Hybrid
Department: IT Platforms | Reports To: Manager, AI Enablement & Automation
ABOUT GENESYS
Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.
We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.
ABOUT THE ROLE
Every sprint that ships depends on someone keeping ceremonies structured, blockers visible, and Jira data trustworthy. Without that, planning drifts, standups run long without resolving anything, and status reports stop reflecting what teams actually shipped. The Scrum Master owns that day-to-day discipline for one or more Platform teams, especially teams still building their agile habits, so the team can focus on delivery instead of process friction.
WHAT YOU'LL DO
Business Analysis & Process Discovery
- Lead discovery sessions, interviews, and workshops with business and IT stakeholders to understand current-state processes, pain points, systems, data, and controls.
- Document current- and future-state processes using BPMN, swimlane diagrams, SIPOC, and value stream maps, and use process mining or task mining data where available to validate how work really happens.
- Write clear business, functional, and non-functional requirements, user stories with acceptance criteria, and process and solution design documents that engineers can build against.
- Build business cases for automation and AI opportunities, estimating effort, hours saved, cost, risk reduction, and ROI, and track realized benefits after go-live.
- Own requirements traceability from business need through build, testing, and release, and manage change requests so scope stays controlled.
Business Process Automation & RPA
- Run the automation intake process, assessing and scoring opportunities for feasibility, complexity, value, and risk, and maintaining a prioritized automation pipeline.
- Recommend the right automation approach for each process, whether RPA (Python and Playwright), API-native integration, browser automation, workflow tools, or AI-augmented and agentic solutions.
- Prepare Process Definition Documents (PDDs) and partner with engineers on Solution Design Documents (SDDs), exception handling, and business-rule definitions.
- Plan and coordinate user acceptance testing, cutover, hypercare, and handover to operations, including runbooks and support documentation.
- Support the health of the existing RPA estate by tracking failures, business impact, and change requests from dependent systems, and feeding modernization candidates into the backlog.
AI Enablement
- Identify, shape, and prioritize AI use cases across business functions, using enterprise AI tools such as Claude, ChatGPT Enterprise, Microsoft Copilot, and Amazon Q, as well as custom AI and agentic workflows.
- Define AI solution requirements, including target users, workflow integration points, data sources, human-in-the-loop steps, success metrics, and measurable quality and acceptance criteria.
- Partner with engineers to define evaluation datasets and test scenarios so AI outputs are validated for accuracy, consistency, safety, and business fit before release.
- Drive adoption through onboarding plans, training materials, user guides, champion networks, and feedback loops, and track adoption and value metrics after launch.
- Operate the AI SDLC for the team, making sure each solution moves through defined stages, from intake and feasibility through data readiness, design, build, evaluation, deployment, monitoring, and retirement, with clear entry and exit criteria.
- Coordinate AI risk classification and impact assessments with Security, Privacy, Legal, and Compliance, and embed required governance checkpoints and approvals into the delivery workflow.
- Maintain the AI use-case inventory and governance documentation, such as risk assessments, data-handling decisions, model and prompt change records, evaluation results, and audit evidence.
- Track post-release monitoring for deployed AI solutions, including quality, cost, incidents, and user feedback, and turn findings into backlog items.
Agile Delivery (Scrum, Kanban & Scrumban)
- Serve as Scrum Master for the AI Enablement & Automation team, facilitating sprint planning, daily standups, backlog refinement, sprint reviews, and retrospectives that stay time-boxed and outcome-focused.
- Select and tailor the right delivery model for each workstream, such as Scrum for project delivery, Kanban for intake, support, and RPA operations, or Scrumban for mixed work, and coach the team on the practices that make it work.
- Design and maintain Jira boards, workflows, WIP limits, Definitions of Ready and Done, and service classes that reflect how the team actually works.
- Track and report delivery and flow metrics such as velocity, sprint goal success, cycle time, lead time, throughput, WIP, and cumulative flow, and use them to drive continuous improvement.
- Identify, escalate, and remove impediments and cross-team dependencies quickly, and follow through on retrospective actions until they are implemented.
- Partner with the Manager, AI Enablement & Automation, as product owner to keep the backlog healthy, well-refined, and ordered by business value and risk.
Stakeholder Management & Reporting
- Act as the main bridge between business stakeholders and the delivery team, setting expectations, communicating trade-offs, and keeping everyone aligned on scope and timelines.
- Track and report team-level delivery metrics (velocity, sprint completion rate, open impediments) using Platform-standard Jira dashboards.
- Produce concise status reports, release notes, and portfolio dashboards covering delivery progress, automation benefits, AI adoption, and governance status.
- Use AI-assisted tools to speed up requirements drafting, process documentation, meeting notes, and reporting, and share effective practices with the wider team.
WHAT YOU BRING
Required Qualifications
- 5+ years of combined experience as a Business Systems Analyst, Business Analyst, or Scrum Master in a technology or IT organization, including exposure to business process automation or AI initiatives.
- Proven business analysis skills, including stakeholder interviews, process mapping (BPMN or similar), requirements elicitation, user story writing with acceptance criteria, gap analysis, and business case development.
- Hands-on experience with business process automation and RPA delivery using platforms such as Automation Anywhere, UiPath, or Microsoft Power Automate, including PDDs, UAT, and handover to operations.
- Practical experience enabling AI solutions in a business setting, such as defining AI use cases, requirements, evaluation criteria, and adoption plans for generative AI tools or AI-augmented workflows.
- Working knowledge of AI governance and responsible AI practices, including risk classification, human-in-the-loop controls, data privacy considerations, and documentation needed for audit and compliance.
- Understanding of the AI SDLC and how it differs from traditional software delivery, including data readiness, prompt and model versioning, evaluations, monitoring, and iterative improvement.
- Strong experience as a Scrum Master applying Scrum, Kanban, and Scrumban, including ceremony facilitation, WIP management, flow metrics, and coaching teams on agile practices.
- Advanced proficiency with Jira and Confluence (or equivalent), including board and workflow configuration, dashboards, and backlog management.
- Excellent facilitation, written, and verbal communication skills, with the ability to explain technical and AI concepts to non-technical audiences and to push back constructively on unclear scope.
Preferred Qualifications
- Scrum certification (CSM, PSM I, or equivalent).
- Familiarity with AI governance frameworks and regulations and with information-security standards such as SOC 2 and ISO 27001.
- Hands-on use of enterprise AI platforms (Claude, ChatGPT Enterprise, Microsoft Copilot, Amazon Q) and awareness of agentic workflows and modern browser automation tools such as Playwright.
- Experience supporting technology teams in IT infrastructure or enterprise environments.
- Comfort with AI productivity tools or interest in applying automation to reduce repetitive work.
- Experience working within an organization with established agile standards.
KEY SKILLS
- Business analysis, process discovery, and requirements management
- Business process automation and RPA opportunity assessment
- AI enablement, AI governance, responsible AI, and AI SDLC management
- Scrum, Kanban, and Scrumban facilitation and coaching
- Jira and Confluence configuration, flow metrics, and delivery reporting
- Stakeholder management and clear communication across business and technical teams
BUSINESS IMPACT
- Ensures automation and AI investment goes to the highest-value opportunities by bringing structured discovery, business cases, and prioritization to the pipeline.
- Improves delivery predictability and speed for the AI Enablement & Automation team through well-run agile practices and visible flow metrics.
- Reduces AI and compliance risk by building governance checkpoints and documentation into the AI SDLC from the start.
- Increases realized value from AI and automation by driving adoption, tracking benefits, and feeding lessons learned back into the backlog.
- Builds consistent delivery habits in teams new to agile, improving sprint predictability over time.
- Keeps delivery moving by resolving day-to-day blockers before they stall a sprint.
- Gives Platform leadership accurate, current delivery visibility through disciplined Jira hygiene and status reporting.
Working hours 3:00 PM-12:00 PM IST
Working at Genesys
- AI at enterprise scale – Build, support and operate AI-powered technology used by more than 8,000 organizations worldwide. 150+ new AI features were released in the last fiscal year.
- A flexible-first culture – Join a global team of nearly 7,000 employees with flexible ways of working designed to help people do their best work.
- Growth in the AI era – Build future-ready skills through mentorship, learning programs, leadership development and education support.
- Time to recharge and give back – Benefits include paid volunteer time, August Free Fridays, well-being resources and regionally tailored programs for employees and their families.
- Recognized globally – Genesys is Great Place to Work® certified in 17 countries and 94% of employees are proud to tell others they work at Genesys.
Learn more about our culture, AI innovation and sustainability commitments through our Careers site and Sustainability Report.
What Happens After You Apply
After you apply, here's what you can typically expect:
- Our Talent Acquisition team reviews your application with the hiring team.
- A Talent Acquisition Partner will review your application and, if your background is aligned, schedule a Zoom interview.
- Next, you'll meet the hiring manager and other members of the interview team.
- We aim to keep the process focused and respectful of your time, with no more than five interviews in most cases.
- After interviews are complete, our team will follow up with the final steps.
Every application is reviewed by a person. Response times may vary by role and location, but our team will keep you informed throughout the process.
Stay Connected
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Be the one building what's next - where AI, experience and impact come together.
Employee Referral
If a Genesys employee referred you, please apply using the link they shared so we can connect your application to their referral.
About Genesys:
Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. Genesys Cloud™ is the Agentic Orchestration Platform that securely connects people, systems, data and AI across the enterprise with built-in governance and control. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces. To learn more, visit www.genesys.ai.
Reasonable Accommodations:
If you require a reasonable accommodation to complete any part of the application process, or are limited in your ability to access or use this online application and need an alternative method for applying, you or someone you know may contact us at reasonable.accommodations@genesys.com.
You can expect a response within 24–48 hours. To help us provide the best support, click the email link above to open a pre-filled message and complete the requested information before sending. If you have any questions, please include them in your email.
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Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, marital status, domestic partner status, national origin, genetics, disability, military and veteran status, and other protected characteristics.
Please note that recruiters will never ask for sensitive personal or financial information during the application phase.
