The Position

This is a hands-on AI applications engineering role dedicated to supporting the CFO organization, spanning finance, accounting, investor relations, payroll, procurement, tax, and internal controls. You'll design, build, and ship AI-powered tools, automation, and data products that power next-generation operations across the CFO organization, elevating how it operates. The scope is deliberately broad. This is a mandate to accelerate the transformation of how our organization works, from the data foundation up. The right candidate is energized by that scale, comfortable navigating complexity across multiple functions, and motivated by driving visible, measurable change across the entire organization. The CFO organization's mission is to be a trusted, business-centric function that shapes the future of OPSWAT by championing high-quality growth, profitability, transformation, and shareholder value. This is not a back-office finance function. It is a strategic, AI-first team of highly skilled professionals who are already advancing in their own AI adoption, with every team member expected to use AI in self-directed, creative ways as a normal part of how they work. This role exists to bring greater depth for the problems that require it: complex engineering, sophisticated data architecture, and AI systems that would be beyond the reach of any individual practitioner working alone.

The CFO organization is an AI-first organization, and we're transforming how that work gets done. Our data spans a wider system footprint than most comparable roles, including NetSuite, procurement tooling, and the operational systems that connect Finance to the rest of the business, such as SugarCRM and DealHub. Building and governing the finance intelligence ecosystem that connects all of these, so trusted data flows cleanly, AI operates on top of it, and financial insight reaches every decision-maker who needs it, is one of the most important infrastructure investments OPSWAT is making. This role owns it.

You'll build, own, and maintain that finance intelligence ecosystem, gathering vetted data from these systems and serving it to dashboards, reports, and AI tools that carry financial insight across the organization. Other members of the CFO organization partner closely with you to vet the data and validate the results, so what flows in is trusted from the start, and live pipelines keep it current automatically. Alongside the ecosystem build, you'll identify and engineer other high-impact AI and automation opportunities across the CFO organization wherever the complexity demands it.

This role operates in a matrix management structure. You will work directly with the Chief Financial Officer and CFO Leadership meetings, ensuring full alignment with finance and accounting strategy and priorities. At the same time, you will report to the head of the Enterprise Applications and Digital Transformation team, to ensure that your work leverages the governed platform and framework that has been developed, avoiding duplicated work and security risks.

How this role works: CFO organization team members own business priorities, define requirements, and provide project direction. They know what needs to be built and why. Your role is to bring technical depth, engineering judgment, and your own ideas to how those requirements are solved, and to proactively identify opportunities the team hasn't yet seen. The vision and roadmap sequencing are collaborative; the architecture and the build are yours. This model means you spend your time engineering, not managing programs, and it works because you are a reliable, visible partner who communicates progress, surfaces risks early, and earns the trust of a highly skilled team through rigorous work. This is not a product management role, a solutions architecture role, or a role that involves managing a team or vendor relationships.

What You'll Own

Finance Intelligence Ecosystem

Architect, build, and own the finance intelligence ecosystem: the interconnected layer of data, AI tools, reports, and agents that serves the entire CFO function. This is not a single application. It is a living, governed ecosystem spanning order-to-cash, procure-to-pay, record-to-report, treasury, tax, payroll, FP&A, and board and investor relations, with every component connected, every data source trusted, and AI operating across all of it. Working from requirements and priorities defined with the CFO organization team, you design how the ecosystem is structured, bring your own technical ideas to how those requirements are solved, and ensure everything stays accurate, current, and built to the standards a public company will require.

AI-Powered Reporting & Decision Support

Build the dashboards, reports, and AI-powered finance applications that deliver insight across the CFO organization and beyond: spend, burn, runway, margin, headcount, bookings/ARR, budget-vs-actual, and the metrics leadership depends on. Layer Claude-powered analytics and natural-language querying on top, so Finance and approved stakeholders can ask questions of the ecosystem directly and get accurate, sourced answers, including variance commentary, anomaly detection, and forecast support drawn from vetted data. The goal is capability diffusion: embedding financial judgment into the tools decision-makers already use, so sound financial thinking reaches every corner of the business without always requiring a Finance partner in the room.

Systems Integration & Live Pipelines

Own the integrations that feed the ecosystem: NetSuite (ERP), Navan (travel & expense), Tipalti (AP and global payments), Carta (equity and cap table), procurement tooling, and the operational systems that connect Finance to the rest of the business, including SugarCRM, DealHub, and HubSpot. Build automated pipelines that keep the ecosystem continuously refreshed, so every report and every AI tool runs on current, trusted data, not yesterday's manual export.

Data Governance, Trust & Access

Establish and maintain the governance layer that makes the ecosystem trustworthy. Define clear, consistent data definitions across every CFO function domain. Partner with the team to validate what flows in and build the controls that keep it accurate over time. Layer role-based, access-controlled sharing on top, offering self-service where it accelerates decisions and controlled access where auditability and compliance demand it. The data that runs through this ecosystem will eventually support external financial reporting and SEC filings, so build accordingly.

Process Automation & Workflow Intelligence

Identify and build AI-powered automation across the CFO function's operational processes, eliminating manual work, reducing cycle times, and improving accuracy across the workflows the team runs every day. Procure-to-pay is an early priority: connecting purchase requests, approvals, vendor and PO data, and payments across procurement, NetSuite, and Tipalti to give Finance a clean, real-time view of committed and actual spend. The same pattern extends across order-to-cash, close and consolidation, payroll reconciliation, and other high-volume, rules-based processes where automation creates the most leverage.

Ecosystem Roadmap

Beyond the initial build, you'll contribute to and execute the roadmap that extends the finance intelligence ecosystem across the full CFO function lifecycle, including procure-to-pay, order-to-cash, record-to-report, close acceleration, and planning and forecasting, with each phase building on the foundation already in production. Roadmap sequencing is collaborative: CFO organization team members set the direction, and you bring technical judgment on how to get there and what's possible. A critical dimension of this roadmap is public company readiness. OPSWAT is on a path to becoming an SEC registrant, and the systems, controls, data integrity, and auditability you build today must be designed to meet that standard. You are building infrastructure that will matter on the day we ring the bell.

Your First 12 Months

We'll give you the context you need and expect you to start delivering impact early. By the end of year one, the CFO organization should be operating measurably differently because of what you built.

Months 1–3: Ship the foundation. Get deep on how the CFO organization works: the processes, the data, the friction points, and the highest-value opportunities across the full function. Establish the working rhythm with CFO org team members. Understand how requirements are defined, how priorities are sequenced, and where your technical ideas add the most value on top of what's asked. You are orienting to build, and building early. By the end of month three, significant improvements to the finance intelligence ecosystem are live: at least one source system feeding automated pipelines, and at least one report or dashboard running on vetted data that the team is actually using. More importantly, the CFO organization has already started to see what this can become.

Months 3–6: Prove the model, expand the foundation. Expand and harden the ecosystem with more integrations, robust refresh pipelines, governance controls, and access frameworks, and onboard real users across the CFO function. By month six, the team is drawing trusted numbers and AI-powered insight directly from the ecosystem, manual reporting work has measurably declined, and the capability diffusion model is demonstrably working: financial insight is reaching decision-makers who previously had to wait for it.

Months 6–12: Scale what works. Scale coverage across more CFO function domains and open governed access to stakeholders across OPSWAT. The ecosystem is now a strategic asset, not just a data tool. Finance is operating as a more influential, proactive business partner because of it. Process automation is eliminating meaningful manual workload. The roadmap for the next phase is defined, grounded in what's already in production, and sequenced with public company readiness in mind. The infrastructure you've built is already approaching the standards OPSWAT will need on the path to becoming an SEC registrant.

This Role Is a Great Fit If You…

• Have 5–8 years of software, data, or AI/ML engineering experience and have shipped production systems.
• Are fluent in Python and strong in data engineering, building pipelines, integrating source systems, and modeling data into clean, well-structured datasets.
• Have hands-on experience with LLMs, RAG, prompt engineering, vector databases, and AI orchestration frameworks.
• Evaluate AI tools with rigor. You test on real finance data, not demos. You know which tools hallucinate on structured financial data, where LLM outputs need guardrails, and how to make an honest call on whether a tool earns its place in a governed ecosystem. In a function where data accuracy has audit and reporting consequences, that judgment matters.
• Bring genuine curiosity about what the data means and how Finance uses it (finance domain experience is not a prerequisite), and you actively build that understanding over time so the tools you build reflect how the business actually works.
• Have built data-backed applications, dashboards, or internal tools with proper access control and governance.
• Are energized working from well-defined business requirements rather than deriving strategy yourself, and bring enough initiative to improve and extend what's asked of you, not just execute it literally. The right candidate sees this as a feature: you spend your time building, not aligning stakeholders or managing roadmaps.
• Measure your success by the change you drive, not the code you ship. A pipeline that runs but doesn't change how the CFO organization operates is not a success. You care about whether Finance is making faster, better decisions; whether insight is reaching leaders who didn't have it before; and whether the team is operating at a higher level because of what you built.
• Are comfortable being held to business outcomes by highly skilled professionals who know their domain deeply. The CFO organization is not a passive user of the tools you build. They are expert partners who will challenge your work, push on data accuracy, and expect you to understand what they're trying to accomplish. You earn their trust through rigorous work and genuine curiosity, and you see that relationship as a strength, not a constraint.
• Build for adoption, not demonstration. You think about the person who has to use what you build on a Tuesday morning under time pressure, and you design for that reality, not for the ideal case. A tool that works technically but sits unused has failed. You actively close that gap.
• Communicate with clarity and confidence at all levels, from technical peers to the CFO. You can translate complex engineering decisions into business terms, present the status and impact of your work without being asked, and raise risks early. You are a trustworthy partner to senior leadership, not just a capable technologist.
• Hold a Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field.

Strong Differentiators

• Experience building governed data platforms, semantic layers, or unified data applications.
• Hands-on integration experience with the finance and operational stack and data lakes/warehouses.
• Strong data modeling and governance background, including semantic layers, data contracts, lineage, validation, and access models. You understand that a finance platform is only as valuable as the trust stakeholders place in it, and you build the controls and documentation that earn and maintain that trust.
• Familiarity with BI tools (Power BI, Tableau).
• Background in cybersecurity or regulated industries where data privacy and access control matter.
• Experience building agentic AI workflows on structured enterprise or financial data, such as LLM integrations with ERP systems, RAG pipelines over finance datasets, Claude-powered natural-language querying on operational data, or AI-driven anomaly detection and variance commentary in a finance context.
• Ability to build without waiting for an IT ticket. Dashboards, automations, agents, and internal tools shipped directly from your own hands. You don't need infrastructure scaffolding to prototype, validate, and deploy. This self-sufficiency is what makes the ecosystem build move fast in a lean org.

What Success Looks Like

• A live application serving vetted finance and operational data through automated, continuously refreshed pipelines.
• Faster, more reliable reporting built on data that's vetted with Finance and kept current automatically.
• Dashboards and reports trusted and used across Finance, with AI-powered analysis on top.
• Governed, access-controlled self-service used by stakeholders across OPSWAT.
• A well-maintained, scalable finance intelligence ecosystem the CFO organization relies on day to day, and that other functions want to replicate.
• Capability diffusion in action: financial insight embedded in the tools leaders across OPSWAT already use, measurably expanding the reach and influence of the CFO organization.
• Infrastructure built to public company standards: auditability, data integrity, access controls, and SOX-ready governance.

Career Path

This role is designed for growth. Successful AI Applications Engineers at OPSWAT build deep expertise at the intersection of AI engineering and financial operations. From this role, you can grow into senior engineering leadership within the Enterprise Applications and Digital Transformation team, or into a broader architecture role spanning all of OPSWAT's internal AI systems. The finance intelligence ecosystem you build here will be foundational infrastructure for the business: designed to public company standards, visible at the highest levels of leadership, and a direct launchpad for what's next.