Senior Business Systems Analyst

Senior Business Systems Analyst

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locations

Tamil Nadu, India

time type

Full time

posted on

Posted Today

job requisition id

JR112515

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 experi