Associate, Finance AI & Automation Solutions

LinkedIn•Mountain View, CA

3d•Hybrid

About The Position

This role will be based in San Francisco or Sunnyvale. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. We are looking for an Associate, Finance AI & Automation Solutions - Low‑Code / No‑Code to design, build, and scale internal applications and automations that improve how Finance teams operate. This role is engineering‑leaning and build‑heavy: you will deliver production workflows and apps using Microsoft Power Apps, integrate them with enterprise systems (including ERP platforms such as Oracle), and apply automation and AI patterns to reduce manual work and increase speed and quality of execution. You will partner closely with stakeholders across Finance functions to understand pain points, translate them into product requirements, and ship iterative solutions with strong reliability, governance, and user experience.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent work experience.
2+ years of experience building applications, automations, or workflow solutions using low-code/no-code platforms.
Experience building production solutions with Microsoft Power Apps or another low-code/no-code platform.
Experience translating business requirements into working applications and workflows.

Nice To Haves

Strong understanding of software delivery fundamentals, including SDLC concepts, environments, testing, and releases.
Experience integrating low‑code applications with enterprise platforms such as Oracle ERP (APIs, data connectors, authentication patterns).
Familiarity with automation tooling and workflow orchestration (approvals, exception handling, notifications, audit trail).
Exposure to AI‑enabled automation use cases and responsible implementation practices.
Experience working in Agile delivery (sprints, backlog grooming, demos, iterative releases).
Experience building solutions for complex, regulated environments with strong controls and governance.

Responsibilities

Build and deploy applications using Microsoft Power Apps (canvas/model‑driven), including user‑friendly interfaces, workflows, and role‑based experiences.
Deliver rapid iterations while maintaining engineering discipline (versioning, environments, release practices, and quality checks).
Design reusable components and patterns to accelerate delivery across multiple use cases.
Automate business processes end‑to‑end (request intake, approvals, task routing, exception handling, audit trail) using low‑code workflow capabilities.
Optimize workflows for scalability, reliability, and maintainability; reduce manual steps and cycle times.
Build and maintain integrations between low‑code apps and enterprise systems (e.g., Oracle ERP), data sources, and downstream tools.
Implement data validations, transformations (lightweight), and error‑handling to ensure accuracy and operational robustness.
Partner with IT/Data teams on integration standards, authentication, and governance.
Identify and implement practical AI patterns within low‑code solutions (e.g., intake classification, summarization, assisted triage, anomaly flags, knowledge search) while ensuring appropriate controls and transparency.
Collaborate with security/privacy and platform teams to apply approved AI services and guardrails.
Own testing and debugging for low‑code solutions: functional validation, performance checks, regression testing, and production issue triage.
Monitor application performance and usage; implement improvements to speed, stability, and user experience.
Provide tier‑2 support and documentation to ensure smooth adoption and ongoing operations.
Run discovery with stakeholders, convert needs into clear user stories/requirements, and manage a prioritized backlog.
Use a product mindset to define success metrics, gather feedback, and iterate based on outcomes.
Communicate progress, tradeoffs, and decisions clearly to drive alignment and adoption.
Ensure applications meet enterprise standards for data protection, access controls, auditability, and change management.
Produce clear technical documentation (solution design, integrations, configuration, runbooks) and user guides.