New opportunity

Senior Business Systems Analyst

Genesys · Tamil Nadu, India

About this role

The Senior Business Systems Analyst acts as a Scrum Master and business systems specialist for the AI Enablement & Automation team, driving process discovery, automation pipelines, and enterprise AI adoption.

Responsibilities

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.
Run the automation intake process, assessing and scoring opportunities for feasibility, complexity, value, and risk, and maintaining a prioritized automation pipeline.
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.
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.
Serve as Scrum Master for the AI Enablement & Automation team, facilitating sprint planning, daily standups, backlog refinement, sprint reviews, and retrospectives.
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.

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, 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.
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 audit documentation.
Understanding of the AI SDLC and how it differs from traditional software delivery, including data readiness, prompt and model versioning, evaluations, and monitoring.
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, including board and workflow configuration, dashboards, and backlog management.
Excellent facilitation, written, and verbal communication skills.

Preferred qualifications

Scrum certification (CSM, PSM I, or equivalent).
Familiarity with AI governance frameworks and regulations and 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.

Working hours are 3:00 PM-12:00 PM IST with a Remote / Hybrid working arrangement based in Tamil Nadu, India.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Business analysisProcess discoveryRequirements managementBusiness process automationRPAAI enablementAI governanceResponsible AIAI SDLC managementScrumKanbanScrumbanJiraConfluenceStakeholder managementAutomation AnywhereUiPathMicrosoft Power AutomatePythonPlaywrightClaudeChatGPT EnterpriseMicrosoft CopilotAmazon Q

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Process Discovery and Requirements Documentation
Lead stakeholder workshops and document current- and future-state workflows using BPMN, value stream maps, and SIPOC, translating findings into precise requirements and user stories with clear acceptance criteria.
AI Enablement and Governance Operations
Shape enterprise AI use cases across business functions, operating the AI SDLC while embedding mandatory risk classification, data privacy considerations, and compliance checkpoints.
Automation Pipeline and Business Case Evaluation
Run the automation intake process to assess feasibility, complexity, risk, and ROI, maintaining a prioritized pipeline for RPA, workflow tools, and generative AI solutions.
Agile Delivery and Scrum Master Facilitation
Facilitate core Scrum ceremonies, manage Kanban flow for operational queues, configure Jira boards, and track flow metrics to drive team predictability and continuous improvement.

Likely challenges to think through

Balancing Traditional Agile with AI SDLC Complexities
The trade-off involves managing traditional software or RPA delivery alongside non-deterministic AI lifecycles, which include prompt versioning, data readiness, and model evaluations. Prepare by demonstrating familiarity with AI-specific testing, human-in-the-loop controls, and iterative model monitoring.

Practice your answers

Technical practice

How do you map current-state and future-state workflows during process discovery?

What to coverCandidates should discuss utilizing process mapping techniques such as BPMN, swimlane diagrams, SIPOC, and value stream maps. Mention how you incorporate process mining or task mining data to validate actual work execution and identify true operational bottlenecks.

What is your approach to writing requirements and managing traceability for automation projects?

What to coverExplain the methodology for authoring clear business, functional, and non-functional requirements alongside user stories with precise acceptance criteria. Discuss maintaining traceability from initial business need through build, testing, and release while controlling scope changes.

How do you evaluate and prioritize automation opportunities in an intake pipeline?

What to coverDescribe how you assess and score opportunities based on feasibility, complexity, business value, and risk reduction. Emphasize building robust business cases that estimate effort, hours saved, and projected ROI.

How does the AI SDLC differ from traditional software delivery lifecycles?

What to coverAddress key distinctions such as data readiness, prompt and model versioning, continuous evaluation datasets, and post-release monitoring. Explain how these elements require iterative improvement compared to standard waterfall or traditional agile cycles.

What are key considerations for AI governance and responsible AI practices in enterprise deployments?

What to coverDiscuss risk classification, human-in-the-loop control points, data privacy considerations, and the documentation needed for compliance and audit trails. Mention coordinating impact assessments with Security, Privacy, Legal, and Compliance teams.

How do you select the appropriate delivery model between Scrum, Kanban, and Scrumban for different workstreams?

What to coverExplain tailoring the delivery framework based on the nature of the work, such as using Scrum for structured project delivery and Kanban for intake, support, and RPA operational queues. Discuss coaching teams on agile habits and flow metrics.

How do you configure and utilize Jira and Confluence to track delivery performance?

What to coverDescribe setting up board workflows, WIP limits, Definitions of Ready and Done, and standard dashboards. Discuss tracking flow metrics such as velocity, cycle time, throughput, and cumulative flow to drive continuous improvement.

What criteria and evaluation methods do you use when enabling generative AI tools or agentic workflows?

What to coverExplain how you define target users, integration points, and success metrics for enterprise AI tools. Discuss partnering with engineers to define test scenarios that validate AI outputs for accuracy, consistency, and safety.

Behavioural practice

Describe a time when you bridged communication gaps between business stakeholders and technical teams.

What to coverUse the Situation, Action, Result framework to share an instance where you aligned non-technical stakeholders and delivery engineers on scope, timelines, and trade-offs. Highlight how you managed expectations and pushed back constructively on unclear requirements.

Tell us about a situation where you had to manage scope creep or changing requirements during a sprint.

What to coverOutline a specific scenario using the Situation, Action, Result structure where a change request threatened delivery timelines. Explain how you evaluated the impact, communicated trade-offs, and preserved traceability and alignment across the team.

Share an experience where you coached a team that was struggling with agile practices or process discipline.

What to coverDescribe a past challenge where team members lacked consistent agile habits, leading to planning drift or unmanaged blockers. Detail the specific facilitation and coaching actions you took, and the resulting improvement in predictability and team focus.

Give an example of how you navigated risk assessment and compliance requirements for a complex technology initiative.

What to coverProvide a Situation, Action, Result example detailing how you collaborated with cross-functional partners like Security, Legal, or Compliance to embed governance checkpoints into a delivery workflow without stalling progress.

Sharpen your knowledge

Topics to prepare

AI SDLC Management and Governance
Conceptualize the entire AI Software Development Life Cycle, including model and prompt versioning, evaluation datasets, and risk classification. Exercise: Draft a risk classification matrix and governance checklist for a generative AI workflow, ensuring compliance and data privacy. Relevance: Required to operate the AI SDLC and coordinate risk assessments with Security and Legal teams.
Business Process Automation and RPA Pipeline Intake
Understand how to evaluate, score, and prioritize automation opportunities based on feasibility, complexity, risk, and ROI. Exercise: Create an intake scoring model and business case template for evaluating candidate processes across RPA and AI solutions. Relevance: Directly addresses the requirement to run the automation intake process and maintain a prioritized pipeline.
Agile Frameworks and Flow Metrics (Scrum, Kanban, Scrumban)
Study delivery models tailored for project delivery versus continuous intake and support workstreams. Exercise: Analyze sample flow metrics (velocity, cycle time, WIP limits) to identify process bottlenecks and prepare retrospective improvement actions. Relevance: Essential for serving as Scrum Master and coaching the AI Enablement & Automation team on agile practices.

Skills to revise

Process Mapping and Requirements Elicitation
Master documenting current- and future-state workflows. Exercise: Construct a BPMN process map and write user stories with clear acceptance criteria based on a simulated stakeholder interview transcript. Relevance: Core requirement for gathering business, functional, and non-functional requirements from stakeholders.
Jira and Confluence Board Configuration
Gain hands-on proficiency in setting up boards, workflows, and dashboards. Exercise: Configure a custom Jira workflow with defined statuses, WIP limits, and dashboards to track sprint and flow metrics. Relevance: Required for maintaining backlog transparency and reporting team-level delivery metrics to leadership.
Process Definition Document (PDD) Preparation
Draft detailed process definitions and solution design documentation for automation initiatives. Exercise: Write a sample Process Definition Document (PDD) outlining manual steps, exception handling, and business rules for an automation candidate. Relevance: Directly tied to partnering with engineers on RPA and workflow automation delivery.

Your preparation checklist

Prepare a Process Mapping and Requirements Walkthrough
Create a sample BPMN diagram and a corresponding set of user stories with acceptance criteria based on a complex enterprise workflow, demonstrating your ability to bridge business needs and technical execution.
Build an Automation and AI Intake Scoring Framework
Develop a structured evaluation matrix and business case template to score automation and generative AI opportunities on feasibility, complexity, risk reduction, and projected ROI.
Draft an AI SDLC and Governance Documentation Package
Prepare sample documentation outlining an AI solution lifecycle, including risk classification, human-in-the-loop control points, evaluation datasets, and audit compliance records.
Design a Jira Board and Flow Metrics Dashboard Configuration
Outline a configured Jira board and workflow setup utilizing WIP limits, Definitions of Ready and Done, and flow metrics such as cycle time and throughput to track team delivery.
Formulate Targeted Questions for the Interview Team
Prepare thoughtful questions regarding how the AI Enablement & Automation team currently balances Scrum and Kanban workflows, manages cross-team dependencies, and collaborates with compliance and security stakeholders.

Availability last checked: 4 Nov 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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