Financial Systems Engineer - Hedge Funds, PE & VC Funds

Junonia Partners•Dallas, TX

10d

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 firm designs controlled financial infrastructure and scalable processes, and is building a finance engineering practice that uses software, data pipelines, and AI to automate fund finance work. Financial Systems Engineers design, build, and operate systems supporting outsourced CFO and Controller engagements. Working with internal teams and directly with clients, the role turns recurring, time-sensitive work into reliable, auditable, automated workflows. The engineer owns projects end to end—from scoping and connecting data sources to building, testing, and deploying solutions with the controls and documentation clients and auditors require. The position calls for understanding fund accounting and the wider objectives of each process, participating in client conversations, and exercising judgment about what to build, buy, automate, or leave to human decision-making. The work spans multiple fund structures, strategies, and technology stacks, and includes responding to production issues and shifting priorities as client needs arise.

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 the relationship between fund administrators, prime brokers or custodians, and OMS platforms.
Demonstrated coding ability, whether coding from scratch or using 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 where human review is needed.
Advanced Excel skills and the ability to turn complex spreadsheets into durable, documented systems.
A controls mindset, 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.
Ability to communicate clearly with finance professionals and technical counterparts in ways that foster strong relationships and trust.
Ability to work in a fast-paced environment and prioritize tasks across multiple clients.
Desire to contribute to an entrepreneurial environment and help build a growing firm into a best-in-class industry partner.
Initiative, interest in building solutions, and accountability 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, or cloud data warehousing, and with workflow automation platforms.
Experience implementing or migrating an ERP, general ledger, or fund accounting system.
A portfolio of tools, automations, or code that can be discussed.

Responsibilities

Analyze opportunities to create autonomous agentic teams that integrate with existing human talent.
Design, build, and maintain data pipelines, workflows, and AI agents for 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 tasks 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 be reused as a starting point for others.
Automate daily and monthly hedge fund cash and P&L reconciliations across OMS, fund administrator, and prime broker or custodian sources; surface breaks with root-cause context; and build tools for 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, and route exceptions to the engagement team.
Support faster, more continuous closes; build audit-ready reconciliations and support schedules; and reduce manual work 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 and integrating fund administrator data delivery, OMS/PMS, accounting, banking, and reporting tools into client operations.
Train Associates, Managers, and Directors to use and extend the tools, increasing the firm's AI fluency.
Respond quickly to production issues and unexpected client operational problems, and shift focus as client needs arise.
Own solutions end to end, including scoping with engagement teams, connecting data sources, building and testing solutions, and moving them into production with appropriate controls and documentation.
Participate in client conversations and use judgment to determine what to build, what to buy, and what should remain a human decision.