3 months ago
Ho Chi Minh City, VietnamSenior / Staff+
Responsibilities
- Architect, build, own, and maintain the finance intelligence ecosystem across CFO functions and enterprise data sources.
- Build automated, continuously refreshed integrations and pipelines for finance and operational systems.
- Create dashboards, reports, and AI-powered finance applications for spend, burn, runway, margin, headcount, bookings, ARR, budget versus actuals, and related leadership metrics.
- Layer Claude-powered analytics and natural-language querying over vetted finance data, including sourced answers, variance commentary, anomaly detection, and forecast support.
- Establish data definitions, validation controls, governance, role-based access, auditability, and compliance-ready data practices.
- Identify and implement AI-powered process automation across procure-to-pay, order-to-cash, close and consolidation, payroll reconciliation, and other operational workflows.
- Partner with CFO organization stakeholders on requirements and priorities while owning the technical architecture and implementation.
- Execute the ecosystem roadmap with scalability, data integrity, access controls, and SEC/SOX-ready public-company standards in mind.
Requirements
- 5–8 years of software, data, or AI/ML engineering experience with production systems shipped.
- Fluency in Python and strong data engineering experience, including pipelines, source-system integration, and structured data modeling.
- Hands-on experience with LLMs, RAG, prompt engineering, vector databases, and AI orchestration frameworks.
- Experience building data-backed applications, dashboards, or internal tools with access control and governance.
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.
- Experience with governed data platforms, semantic layers, unified data applications, finance or operational system integrations, data modeling, governance, data contracts, lineage, validation, and access models is a strong differentiator.
- Familiarity with Power BI or Tableau is preferred.
- Cybersecurity or regulated-industry experience involving data privacy and access control is a differentiator.
- Experience building agentic AI workflows, RAG pipelines, LLM integrations with ERP systems, AI-driven anomaly detection, or finance-focused variance commentary is preferred.
- Ability to independently prototype, validate, deploy, and ship dashboards, automations, agents, and internal tools.
Tech Stack
Categories
AI ApplicationsData Engineering
About OPSWAT
OPSWAT builds cybersecurity software for critical infrastructure, delivering malware prevention, content disarm and reconstruction, secure file transfer, and device access control across IT, OT, and ICS environments. It sells enterprise software and SaaS platforms to public- and private-sector organizations worldwide. Founded in 2002 and headquartered in Tampa, Florida, the privately held company is used in regulated industries such as energy, government, and finance.