Financial Systems Engineer - Hedge Funds, PE & VC Funds

Junonia Partners•Dallas, TX

11d

About The Position

Junonia Partners provides outsourced CFO and Controller services to investment advisors across hedge funds, private equity, venture capital, and institutional investors. The Financial Systems Engineer works at the intersection of fund accounting and software, designing, building, and operating systems that support outsourced CFO and Controller engagements. The role turns recurring, time-sensitive finance work into reliable, auditable, automated workflows and anticipates changes in AI tools and industry practices so that systems remain adaptable and valuable. The position owns solutions end to end: scoping problems with engagement teams, connecting data sources, building and testing systems, and moving them into production with the controls and documentation required by clients and auditors. It involves close collaboration with the firm’s team and direct participation in client conversations. The engineer applies judgment about what to build, what to buy, and what should remain a human decision; automated outputs require appropriate finance rules, review, and sign-off. The work spans multiple fund structures, strategies, and technology stacks, including hedge funds, private equity, venture capital, fund and management company finance, reporting, close, audit, tax, and fund launches. The role also maintains reusable workflows, supports production issues, and trains colleagues to use and extend the tools. Advancement is performance-driven and based on demonstrated impact.

Requirements

3–5+ years of experience in the alternative investment management industry, such as hedge funds, private equity, venture capital, fund administration, or fund audit, in a role with meaningful systems, data, or automation responsibility.
Working knowledge of fund accounting, including NAV calculation, investor capital allocations, management and incentive fees, capital calls and distributions, and relationships among fund administrators, prime brokers or custodians, and OMS platforms.
Demonstrated coding ability, whether coding from scratch or with AI assistance, and the ability to read and debug code.
Experience working with APIs, data files, and integrations between financial systems.
Demonstrated use of AI tools in real finance workflows, including building prompts, skills, agents, and automations used by others, with judgment about when AI output requires human review.
Advanced Excel skills and ability to translate complex spreadsheets into durable, documented systems.
Exceptional attention to detail, a habit of testing and documenting work, and understanding of what auditors need to rely on an automated process.
At least a Bachelor’s degree in Accounting, Finance, Computer Science, Engineering, or a related quantitative field, with strong academic credentials.
Experience defining, creating, and implementing processes and systems from the ground up.
Clear communication with finance professionals and technical counterparts, fostering strong relationships and trust.
Ability to work in a fast-paced environment and prioritize tasks across multiple clients.
Desire to work in an entrepreneurial environment and help build a growing firm; the role suits someone who takes initiative, builds solutions, and is accountable for outcomes.

Nice To Haves

CPA, CFA, or equivalent technical accounting credential.
Experience with industry platforms such as Enfusion, Eze, Geneva, Allvue, Investran, or Carta, and related data delivery automations.
Experience with BI and data tools such as Power BI, Metabase, cloud data warehousing, and workflow automation platforms.
Experience implementing or migrating an ERP, general ledger, or fund accounting system.
A portfolio of tools, automations, or code that the candidate can walk through.

Responsibilities

Analyze opportunities to create autonomous agentic teams that integrate with existing human talent.
Design, build, and maintain data pipelines, workflows, and AI agents supporting hedge fund, private equity, and venture capital engagements.
Connect client and service-provider systems through APIs, SFTP, report exports, and data feeds, including OMS/PMS platforms, fund administrator portals, prime broker and custodian files, bank portals, payroll, and accounting systems.
Build reusable AI skills and agents for recurring work such as data pulls, reconciliations, document review, variance analysis, and first-draft deliverables.
Maintain a shared library of firm workflows so solutions developed for one client can serve as a starting point for other clients.
Automate daily and monthly hedge fund cash and P&L reconciliations between OMS, fund administrator, and prime broker or custodian; surface breaks with root-cause context; and build tools supporting treasury management, margin, financing, and locates.
Build private equity and venture capital models and tools to recalculate capital calls, distributions, management fees, carried interest, and distribution waterfalls; track investor commitments and unfunded balances; and streamline portfolio company data collection and valuation support.
Automate review of NAV packages and investor statements, including shadow recalculation of investor allocations, management fees, and incentive allocations, routing exceptions to the engagement team for review.
Help clients move toward a faster, more continuous close; build audit-ready reconciliations and support schedules; and reduce manual effort for annual fund and management company audits and tax processes.
Build live reporting, cash forecasts, budgets, and dashboards for management company clients.
Ensure automated numbers have traceable sources, documented calculations, and clear human approval points; build monitoring, exception reporting, and regression testing.
Support fund launches by evaluating and implementing technology stacks, including fund administrator data delivery, OMS/PMS, accounting, banking, and reporting tools, and integrating them into client operations.
Train Associates, Managers, and Directors to use and extend the tools, increasing AI fluency across the firm.
Respond quickly to production issues and unexpected client operational problems, shifting focus as client needs arise.