Financial Systems Engineer

Star Mountain Capital•Tampa, FL

About The Position

The Financial Systems Engineer works at the intersection of financial operations, fund finance, and applied AI engineering, embedding with the CFO and finance leadership to turn core financial workflows into AI-engineered automations and scalable financial products. The role supports fund operations, reporting, and infrastructure as the firm grows, and requires both engineering depth and fluency in how a private investment firm operates, including funds, investors, deals, and portfolio companies. It collaborates with enterprise, technology, and internal engineering teams and operates at the senior end of the finance function. The position analyzes finance and fund-management workflows, architects and builds financial technology infrastructure, and designs, prototypes, and deploys automations and financial products. It bridges finance stakeholders and engineering execution, establishes frameworks for evaluating and maintaining automations, and documents workflows, architecture, and tooling decisions. It may also contribute to integrated systems spanning fund operations, investor reporting, deal, portfolio, and data workflows.

Requirements

1–3 years of full-time experience combining engineering and financial services; backgrounds in banking, management consulting, fintech, or private equity are considered.
Demonstrated ability to build and ship software in production environments, with hands-on experience in data pipelines, APIs, or workflow automation.
Finance fluency sufficient to understand how a private investment firm operates, including funds, investors, deals, and portfolio companies.
A degree or demonstrated proficiency in Computer Science, Software Engineering, Applied Mathematics, or a comparable quantitative field.
Working command of Python or an equivalent language, and comfort with structured data manipulation, automation tooling, and system integration.
Ability to design systems that are documented, maintainable, and scalable beyond the individual contributor.
Exceptional attention to detail so that outputs can be trusted by finance leadership without re-checking.
Comfort operating in ambiguity and building structure where none exists.
Clear written and verbal communication, including comfort presenting technical work to senior finance and executive stakeholders.
Strong organizational skills and ability to manage multiple workstreams, competing priorities, and defined delivery standards simultaneously.
Discretion and sound judgment when handling confidential fund, investor, and financial information.
Team-oriented, positive, solutions-based attitude and strong work ethic.

Nice To Haves

Recent graduates with strong technical credentials and finance exposure are encouraged to apply.
Familiarity with AI/ML frameworks or LLM-based tooling; applied experience building with or deploying AI systems is strongly preferred.

Responsibilities

Analyze fund management and finance operations workflows end-to-end to identify and prioritize opportunities for AI-driven automation and process redesign.
Partner with the CFO and finance unit to architect and build financial technology infrastructure, including automated reporting pipelines, fund data systems, and AI-assisted financial tooling.
Design, prototype, and deploy AI-engineered automations and financial products; translate finance requirements into technical specifications and engineering outputs into finance-ready solutions.
Collaborate with enterprise, technology, and engineering teams to integrate financial tooling into the firm’s technology stack and data architecture.
Bridge finance stakeholders and engineering execution by presenting solutions clearly to non-technical leadership and documenting decisions for team-wide adoption.
Establish repeatable frameworks for evaluating, implementing, and maintaining financial automations; document workflows, system architecture, and AI tooling decisions.
Help build integrated systems across the platform, including fund operations, investor reporting, deal, portfolio, and data workflows, so tools, data, and processes connect and scale with the firm.