Senior Business Systems Analyst

Be the one building AI-powered experiences where they matter most.

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:

• 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.
• 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.
• 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.
• 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.
• 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:

• 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.
• 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.

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