Senior Associate Product Delivery - Business Enablement

Be at the heart of transforming visions into market-ready products, while you navigate through and solve complex challenges. In this dynamic environment, you ensure smooth product delivery and support change initiatives, marking a significant step in your career growth and innovation journey.

As a Senior Product Delivery Associate within the Client Onboarding and Service (COS) Product team, you are trusted with enabling the delivery of products in a stable and scalable way. You will work with cross-function teams, build key relationships, and enable the product to continuously deliver value. You will identify and deliver impactful solutions across onboarding, servicing, and contact center journeys. You will partner with cross-functional teams to translate operational challenges into actionable, AI-driven improvements, fostering a culture of innovation and continuous enhancement.

Job responsibilities

• Lead interviews, call listening, and journey mapping across onboarding, servicing, and contact center channels (voice, chat, email, self-service)
• Translate operational pain points into clear hypotheses with measurable business outcomes, including cycle time, exception rates, containment, FCR, AHT, ASA, abandon rates, QA pass rates, and CSAT/NPS
• Prioritize opportunities based on value, feasibility, risk, and client impact, defining success criteria and guardrails
• Collaborate with Operations, Product, and Risk to ensure solutions address real workflow friction
• Design structured prompt patterns and interaction flows for agent assist, case triage, classification, summarization, and document processing
• Specify retrieval and grounding approaches, define expected AI behaviors, and establish escalation criteria
• Write user stories that define inputs, outputs, edge cases, and acceptance criteria grounded in operational reality
• Create evaluation rubrics covering quality, factuality, helpfulness, safety, tone, and compliance
• Build and maintain curated test sets with clear error taxonomies and severity definitions
• Define offline evaluation standards and support online experiments (A/B tests, champion challenger)
• Design Human-in-the-Loop workflows, reviewer guidelines, calibration routines, and QA sampling methods

• 3+ years of experience or equivalent expertise in product management or a relevant domain area
• Experience executing operational management and change readiness activities
• Experience in product deployment processes
• 5+ years of experience in product ownership, business analysis, service design, consulting, or operations within financial services or a regulated environment
• Strong functional understanding of client onboarding, servicing, and/or contact center operations
• Proven ability to translate business problems into clear, measurable requirements and acceptance criteria
• Hands-on experience designing prompts, defining evaluation criteria, and operating human-in-the-loop review in pilot or production AI use cases
• Familiarity with common AI capability patterns (retrieval grounded assistants, summarization, classification, document extraction) and when to apply rules, retrieval, or learning
• Command of onboarding and service metrics and levers: cycle time, exceptions, containment, FCR, AHT, ASA, abandon, QA, CSAT/NPS
• Experience interpreting offline evaluation results and online experiment outcomes to drive decisions
• Excellent stakeholder management across Operations, Contact Center, Product, Data, Technology, Risk, and Compliance

• Developed knowledge of the product development life cycle
• Experience building gold sets, error taxonomies, reviewer playbooks, and calibration frameworks
• Working knowledge of retrieval, grounding, and prompt safety patterns; awareness of common failure modes and mitigations
• Familiarity with BI tools and KPI dashboards; ability to interpret analytics or basic SQL outputs
• Background in service blueprinting, Lean/continuous improvement, or change management
• Understanding of model risk management and responsible AI practices in regulated environments