AI Engineer - Finance

Job Description

The AI Engineer - Finance is an embedded AI partner within Lineage's Finance organization, the professional who sits at the intersection of the AI platform and finance and accounting problems. Reporting to the Chief Accounting Officer and working directly with the broader finance team, this role works with the finance team to identify high-value AI finance use cases, builds first solutions alongside finance teams where needed, and teaches those teams to build, run, and improve their own, so capability stays in Finance. These AI solutions will make our finance professionals more productive and make our processes more accurate, efficient, and well controlled. Success is measured by team adoption and self-sufficiency, not solely by solutions delivered. The role has a dotted-line relationship to a Senior Forward Deployed Engineer in Lineage's enterprise AI Center of Excellence (CoE) and builds/teaches in accordance with the standards, platforms, and governance established by the AI CoE.

This is a REMOTE role.

We are unable to sponsor work authorization, now or in the future, for this role.

Primary

Responsibilities

• Partner and discover: Embed with Finance and Accounting stakeholders (e.g., controllership, financial reporting, FP&A, tax, audit, and treasury) to deeply understand workflows, pain points, and opportunities for AI-driven improvement.
• Grow and maintain a broad and deep knowledge of finance and accounting processes, Lineage's supply chain business, and the ways AI can be applied to them.
• Teach and enable: Enable and upskill Finance team members to adopt AI tools effectively and identify new opportunities for AI-driven improvement.
• Work with CAO and other finance leaders for ideas including, but not limited to, workshops, holding office hours, reusable guides and templates, champion network, hosting a hack-a-thon, etc. Coach teams to build and own their own solutions, and move from "building for" to "building with" over time.
• Build and deliver: Collaborate with stakeholders to quantify use-case value and , prioritize the engagement pipeline, and measure post-deployment impact. This includes identifying "quick wins" and situations where a short-term solution will provide benefit while a longer-term solution maybe developed in the future. Additionally, work with teams in existing systems, including those that leverage AI, to further leverage existing functionality and supplement with additional prompts, skills, and/or agents, as needed.
• Identify places where AI solutions require a broader skillset and then sScope, architect, and deliver end-to-end AI solutions, from data ingestion, prompt engineering, skill and agent build through deployment, monitoring, and iteration.
• Govern and control: Provide software engineering and AI solutions excellence including:
• Leverage the CoE's core AI platform, working closely with Platform Engineers to extend tooling and surface platform gaps.
• Follow and apply the AI CoE's standards for architecture, development, security, data governance, model evaluation, and responsible AI; partner with the dotted-line Senior Forward Deployed Engineer on design and code reviews, technical guidance, and alignment with enterprise AI priorities.
• Ship flagship finance use cases (e.g., month-end close, account reconciliations, journal entry support, variance analysis, and reporting) that establish repeatable delivery patterns.
• Design solutions that support internal controls, auditability, and SOX compliance, including appropriate human review, documentation, and data access controls.
• Measure and scale: Help the finance team quantify value, potential cost savings, and track adoption/self-sufficiency metrics.
• Other Technical Objectives:
• Partner with Solutions Architects and Data & Integration Engineers to ensure solutions integrate cleanly with enterprise systems and finance data sources (e.g., ERP, consolidation, and reporting systems).
• Document solution architectures, runbooks, and lessons learned to accelerate future engagements and enable developer enablement across the enterprise.
• Consistently deliver high-quality software and processes in usable increments.

Education and Work

Experience

• Bachelor's degree in computer science, software engineering, or a related field, or equivalent practical experience.
• 4+ years of experience in software engineering, applied ML/AI, or solutions engineering, with direct client- or stakeholder-facing delivery.
• Experience with enterprise AI platforms such as Claude Enterprise, OpenAI (ChatGPT Enterprise), or other similar tools is a plus.
• Proficiency in Python and experience with modern AI/ML tooling (LLM APIs, agent frameworks, vector databases, RAG pipelines).
• Demonstrated ability to take a project from an ambiguous business need to a production-grade solution with minimal oversight.
• Experience working in fast-paced, early-stage, or consulting-style environments where scope and priorities shift frequently.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and modern data infrastructure.
• Track record of shipping AI/ML use cases in enterprise environments (financial services, healthcare, manufacturing, logistics, or similar) is a plus.
• Experience building with agentic AI frameworks (e.g., LangChain, CrewAI, AutoGen) and evaluating model outputs systematically is a plus.
• Previous exposure to finance and accounting systems (e.g., ERP, general ledger, consolidation, close management, and reporting tools) is a plus.
• Understanding of accounting principles (U.S. GAAP), the financial close process, and internal controls (SOX) is a plus.

Required Skills and Abilities

• Demonstrate excellent verbal and written communication skills, including the ability to present to business leaders and translate technical concepts.
• Manage stakeholder relationships and expectations across multiple engagements.
• Possess a willingness to be coached and proactively seek feed