Transform how Operations work gets done by delivering intelligent automation and responsible artificial intelligence solutions end to end. In this role, you will directly reduce manual intervention, improve control outcomes, and build scalable capabilities that can be adopted across regions. You will partner closely with Operations and Technology to turn complex processes into measurable, sustainable improvements. If you thrive on ownership, rigor, and real-world impact, we would like to meet you.
Job summary
As an Automation Associate in Operations Intelligent Automation, you will own automation initiatives from discovery through stabilization, delivering measurable improvements in efficiency, quality, and control outcomes. You will join us in building scalable solutions that can be rolled out across regions and sustained by Operations post go-live. You will be assessed primarily on one of two tracks: Business Analyst (Automation Delivery) or Engineer (AI/Automation Build), and you will bring deep strength in the track you select. You will help us digitize processes with strong documentation, testing discipline, and production readiness so we can deliver safely and consistently.
**Job responsibilities **
- Own automation initiatives end to end, including discovery, solution design, build/enablement, testing and user acceptance, release, and stabilization
- Partner with Operations and key stakeholders to elicit user requirements, target outcomes, and SLAs; run workshops/interviews to capture current-state and pain points.
- Author and maintain a layered requirements stack including user requirements, functional requirements, and technical solution design inputs, and ensure obtain consensus across stakeholders
- Define measurable success metrics (for example, time saved, error reduction, service level improvement, control uplift) and track outcomes
- Ensure solutions are control-aligned and audit-ready with appropriate documentation including maintaining as-is/to-be process models (BPMN), define control points and exception handling aligned to cutoffs and client SLAs; specify upstream/downstream integrations)
- Design for multi-region rollout, reusability, and sustainable adoption by Operations, establishing end-to-end traceability from requirements to epics/stories, tests, and releases; enforce taxonomy, versioning, and change control; define testable acceptance criteria and support UAT/defect triage.
- Lead deep-dive process discovery (as-is workflows, inputs/outputs, exception paths, volumes, failure points) aligned to your track
- Translate business needs into executable delivery artifacts (requirements or technical design) aligned to your track
- Build or enable automation and artificial intelligence solutions using fit-for-purpose approaches with strong safety and testing discipline
- Implement robust exception handling, logging, monitoring, and performance considerations for production-grade delivery
- Coordinate cross-functional delivery activities and manage dependencies, risks, and decisions to keep delivery on track
- Document decisions, controls, testing evidence, and support model to enable stable operations post go-live
- Learn and utilize the firm’s latest approved AI capabilities; define AI-specific functional requirements (guardrails, evaluation, HITL) and design inputs (inference integration, observability).
Required qualifications, capabilities, and skills:
- 5 years delivering automation-focused business analysis in financial services or other controls-driven environments
- 5 years producing clear, implementable requirements (for example, business requirements documents, user stories, acceptance criteria) that engineering teams can execute with minimal ambiguity
- 3 years embedding operational risk, controls, and audit evidence requirements into solution design and documentation
- 3 years designing and implementing integrations (for example, services or application programming interfaces) with robust exception handling, logging, and monitoring
- 3 years of proficiency with JIRA/Confluence, BPMN/UML, API specifications (e.g., OpenAPI)
- Strong proven ability to learn enterprise AI platforms and align to firm-wide governance—focused on scaling adoption, not model-building.
- A strong ability to partner with stakeholders across Operations and Technology, translating needs into deliverables and decisions
Preferred qualifications, capabilities, and skills:
- Experience supporting business-wide AI adoption (playbooks, change management); familiarity with data governance, entitlements, operational resilience, and records management.
- Certifications such as CBAP/BCS BA; relevant AI/ML coursework a plus.
- Hands-on experience with workflow or robotic process automation platforms
- Hands-on scripting experience (for example, Python) to support automation delivery and prototyping
- Experience with data analysis or visualization tools (for example, Alteryx, Tableau, or equivalents)
- Experience delivering automation at scale across regions or business lines, including training, adoption, and operating model readiness
- Experience evaluating artificial intelligence tooling pragmatically, including safety, controls, and testing approach
- Experience designing configuration-driven, reusable solutions that handle regional variation with minimal ongoing dependency
- coding and engineering experience delivering production-grade automation or artificial intelligence-enabled solutions