Staff, Finance AI & Automation

Job description

Job Description
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 a finance builder - someone who knows how enterprise finance actually runs, can walk into a process and immediately see where the friction lives, and has the energy and product instinct to go fix it.
This is not an engineering role. You will not be architecting ERP systems, writing production code, or owning platform infrastructure - our engineering and IT partners do that. You are the person who sits with the Controller, the FP&A lead, or the Collections manager, understands why the close takes four days longer than it should, and then builds the thing that fixes it using AI tools, low-code platforms like Microsoft Power Apps and Power Automate, and capabilities our engineering teams have already built for us.
This person may have come from consulting, from product management, from a finance operations seat, or from a liberal arts background and learned to build along the way. What matters is that you have shipped real things that real business users adopted, and that you are genuinely fluent in the language of finance: the close, the forecast, the PO lifecycle, the accrual, the collections aging bucket.
You will partner across Finance - Strategic Finance, Controllership, Procurement, Marketing Finance, and Collections and across our systems landscape (Oracle Fusion ERP, Oracle EPM, GetPaid, Allocadia) to find the highest-friction work and replace it with something better.
Responsibilities
Find the friction

• Embed with Finance teams to map how work actually gets done — not how the process document says it does — and identify where time, rework, and manual effort are being lost.

• Build and maintain a prioritized view of the highest-value automation and AI opportunities across the finance function, sized by impact and effort.

• Bring a point of view. You are expected to propose what should be built, not wait to be handed requirements.
Build the solution

• Design and ship working applications and workflows using low-code/no-code platforms (Microsoft Power Apps, Power Automate) and approved AI services — configuration and assembly, not software development.

• Apply AI where it genuinely helps: summarization, document extraction, classification, anomaly and exception detection, narrative and commentary drafting, guided search across finance knowledge.

• Use platforms, connectors, and services our engineering and IT partners provide, rather than building custom infrastructure yourself. Know where your build stops and theirs begins.

• Start small, ship fast, iterate in the open. A working prototype in front of a stakeholder beats a perfect requirements document.
Own the outcome

• Define what success looks like before you build cycle time saved, error rate reduced, manual touches eliminated, adoption — and measure it after.

• Drive adoption: train users, write the guides, sit with the team in week one, and refine based on what they actually do.

• Keep what you ship healthy monitor usage, fix what breaks, retire what stops earning its keep, and escalate to engineering/IT when something needs a real platform solution.
Partner and influence

• Work as a trusted partner to finance leaders: run discovery, frame trade-offs, manage expectations, and say no to the low-value asks so the high-value ones ship.

• Collaborate with IT, Data, Security, and Privacy partners so that what you build meets enterprise standards for access, data protection, auditability, and responsible AI use.

• Operate comfortably in a SOX-controlled environment — understand segregation of duties, change management, and audit trail as design constraints, not obstacles.
Scale the capability

• Create reusable patterns, templates, and playbooks so each solution makes the next one faster.

• Help build a builder culture inside Finance — coach and enable others on the team to use these tools themselves.

Qualifications
Basic Qualifications

• Bachelor's degree or equivalent practical experience.

• 8+ years of experience in finance, business operations, product management, consulting, or transformation roles.

• Demonstrated experience building and shipping solutions that business users adopted applications, workflows, tools, or automations whether on low-code platforms, AI tools, or off-the-shelf platforms.

• Working knowledge of core enterprise finance processes (e.g., close and consolidation, planning and forecasting, procure-to-pay, order-to-cash, or marketing finance).

• Experience using AI tools in a real work context to produce a working product
Preferred Qualifications

• Experience in a finance function at a large, c

Interview problems reported for LinkedIn

Reported by candidates and public write-ups, not by LinkedIn. Practise each one here:

• Maximum Subarray — Medium
• Valid Parentheses — Easy
• Number of Islands — Medium
• Maximum Product Subarray — Medium
• Minimum Window Substring — Hard
• Search in Rotated Sorted Array — Medium
• Lowest Common Ancestor of a Binary Search Tree — Medium
• Maximum Depth of Binary Tree — Easy
• Serialize and Deserialize Binary Tree — Hard
• Merge Intervals — Medium
• Two Sum — Easy
• Merge Two Sorted Lists — Easy
• Merge K Sorted Lists — Hard
• Binary Tree Level Order Traversal — Medium
• Insert Interval — Medium
• Product of Array Except Self — Medium
• House Robber — Medium
• Palindromic Substrings — Medium
• Graph Valid Tree — Medium
• Number of Connected Components in an Undirected Graph — Medium
• Longest Substring Without Repeating Characters — Medium
• Same Tree — Easy
• Reorder List — Medium
• Invert Binary Tree — Easy
• Combination Sum — Medium
• Course Schedule — Medium
• House Robber II — Medium
• Word Break — Medium
• Unique Paths — Medium
• Best Time to Buy and Sell Stock — Easy
• Longest Consecutive Sequence — Medium
• Find Minimum in Rotated Sorted Array — Medium
• Reverse Linked List — Easy
• Linked List Cycle — Easy
• Validate Binary Search Tree — Medium
• Kth Smallest Element in a BST — Medium
• Longest Palindromic Substring — Medium

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