Wealth Management Operations-Transformation-Albany-Associate

Goldman Sachs•Albany, NY

15d•$60,000 - $100,000•Onsite

About The Position

Wealth Management Operations is seeking a motivated Associate to support our Applied AI and low-code initiatives, driving the practical convergence of advanced AI capabilities, workflow automation, and analytics to deliver measurable operational, risk, and experience improvements across the division. You will be responsible for creating advanced AI prompts and AI agents that enhance operational performance within the firm's approved AI solutions, implementing automation and analytics using low-code tools, and designing workflows using BPMN-style process modeling within Goldman Sachs's workflow platforms. Working under the guidance of senior team members, you will help translate business needs into deployable AI-enabled and automated solutions. You will contribute to the design, development, and deployment of human-in-the-loop "AI Assistants" through a controlled, risk-aware lifecycle — from ideation and prompt engineering through piloting, governance review, and production rollout. In parallel, you will build automated workflows and self-service analytics that streamline operational processes and empower business users. You will collaborate with business stakeholders, Operations BI teams, Technology, Risk & Compliance, and team leadership to help deliver scalable AI, automation, and workflow solutions aligned with organizational goals.

Requirements

Bachelor’s STEM degree
Minimum 3 years of experience in applied AI, business intelligence, data analytics, process automation, or related discipline (financial services or wealth management a plus).
Hands-on experience with prompt engineering and AI agents with enterprise AI platforms (e.g., Microsoft Copilot).
Experience with low-code/no-code tools for automation and analytics (e.g., Power Platform, Alteryx, Tableau, Power BI, or similar).
Familiarity with BPMN-style process modeling and workflow design tools.
Strong analytical skills and the ability to translate business needs into technical solutions.
Solid understanding of data governance, data quality, and regulatory compliance in a financial services context.
Effective collaboration skills across business, technology, and operations teams.

Nice To Haves

Experience in Wealth Management or Financial Services operations and technology.
Exposure to LLM-based applications, retrieval-augmented generation (RAG), and agentic AI frameworks.
Practical experience with BPMN workflow platforms (e.g., Camunda, Appian, or similar).
Relevant certifications in low-code platforms, BPMN, AI platforms

Responsibilities

Create advanced, well-engineered prompts and AI agents within the firm's approved AI platforms (e.g., Copilot, LLM-based tools), contributing to prompt libraries and reusable templates that maximize out-of-the-box solution value.
Support the development of human-in-the-loop AI Assistants that augment employee and client-facing workflows, ensuring appropriate human oversight, escalation paths, and feedback loops.
Assist in testing, validation, and iterative refinement of prompts and AI Assistants across the solution lifecycle (use case intake, feasibility, prompt engineering, testing, risk review, pilot, and production).
Implement automation and analytics using low-code and self-service tools to democratize data access, accelerate report development, and empower users.
Build and maintain dashboards, reports, and automated data flows that deliver actionable insights to business stakeholders.
Support data quality, lineage, and governance standards across BI and automation assets.
Design, document, and build workflows using BPMN-style process modeling within Goldman Sachs's workflow platforms.
Translate business requirements into clear, structured process models, identifying opportunities to automate manual steps.
Partner with process owners to test, refine, and deploy workflows, ensuring alignment with the division's target operating model.
Contribute to business cases for new AI Assistants, automation, and analytics products, including efficiency gains and KPI frameworks.
Collaborate with cross-functional teams — including business analysts, data engineers, prompt engineers, BI developers, and subject matter experts.
Uphold governance, data privacy, and regulatory compliance standards across all AI, automation, and workflow deliverables.
Identify synergies between AI, automation, and analytics to enhance overall solution value.