Data Engineer with AI

Position : Data Engineer With AI

Location: USA (Remote)

Duration: Long Term Contract

• Own end-to-end delivery: design, build, test, iterate, and deploy AI-enabled solutions from first conversation to production release
• Translate business needs into technical solutions: understand Finance requirements deeply, guide stakeholders on solution design, and architect implementations grounded in Client's technology stack
• Embed governance from day one: implement guardrails, fallback behaviors, human- in-the-loop logic, and documentation that satisfies enterprise control and audit requirements
• Build stable data foundations: identify and integrate relevant datasets into extensible pipelines that power reliable automation
• Collaborate across disciplines: partner with internal architects on design decisions, debug issues directly with stakeholders, and bring field learnings back to improve the Hub's platforms and practices
• Document with intent: record technical decisions, assumptions, and dependencies so that every solution is auditable, maintainable, and transferable
• Participate in oncall rotation for close cycles: work as part of our oncall team to support month-end and quarter-end activities as needed, which may include after-hours and weekend coverage according to a pre-set plan, ensuring critical Finance workflows run without disruption

• Strong software engineering skills in Python, SQL, and API development
• Hands-on experience with AI/ML models, LLMs, or intelligent automation frameworks
• Comfort with modern AI development tools including agentic frameworks, AI workflow builders, and "vibe-coding" environments (e.g., Claude Code, Cursor, n8n, or similar)
• Working knowledge of data pipelines and integration patterns that move data reliably between systems
• Understanding of enterprise controls and audit requirements: you know how to build things that pass compliance review, not just demo well

• Ability to work directly with Finance stakeholders who aren't engineers, translating their pain into your architecture
• Track record of breaking down loosely defined business challenges into structured, repeatable technical solutions
• Strong communication skills: you can explain technical tradeoffs, design choices, and risk in plain language