Forward Deployed Engineer

Maybern is transforming the way private fund managers effectively manage their funds through cutting edge technology. Maybern is founded by top engineering experts with deep knowledge of the fund management space.

Private funds manage $15T in capital and are growing at 20% YoY, but with increasing regulatory scrutiny and investor demands for transparency, the need for world class software to help private fund CFOs is crucial.

This is where Maybern comes in.

We are equipping fund managers with intuitive, flexible fund management software, enabling private investment managers to focus on what they do best: driving returns for their investors. We are backed by leading venture capital firms and a large number of strategic investors.

Maybern is an NYC based company with a strong in-office culture to drive collaboration, and we are looking to make strong additions to our team.

Maybern is building a brand new Forward Deployed Engineering function to work directly with customers on strategic applications that extend the Maybern platform. This team sits at the intersection of customer deployment, applied AI, quantitative modeling, and product development. The work includes custom applications, analytical systems, scenario tools, forecasting workflows, optimization engines, and other high-value extensions for sophisticated private-markets customers.

We are looking for a strong Forward Deployed Engineer who can independently own meaningful customer work. This is a builder role for someone who can move from vague requirements to working systems, partner effectively with stakeholders, and balance speed with rigor.

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  Lead scoped forward-deployed engagements from discovery through deployment and iteration

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  Design and build custom applications, workflows, and decision-support tools for Maybern customers

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  Work across AI, machine learning, forecasting, scenario modeling, optimization, and workflow automation

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  Partner directly with customer stakeholders to refine requirements and drive adoption

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  Build reliable evaluation, validation, and monitoring layers for AI and quantitative systems

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  Create reusable abstractions, internal libraries, and common patterns from customer-specific work

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  Mentor Associate Forward Deployed Engineers on delivery and problem structuring

• Builder. You ship reliable systems end-to-end and decide well between speed and rigor.

• Customer-Oriented. You take ambiguous requirements and turn them into structured technical plans and trust with stakeholders.

• Quantitatively Strong. You apply solid quant reasoning to real-world problems and know where ML / LLMs help vs. don't.

• Partner. You collaborate well across product, engineering, and customer teams and mentor junior teammates with care.

• Curious. You're excited by hard problems at the intersection of AI, quantitative methods, and customer impact.

• 1–4 years of experience in software engineering, ML engineering, data engineering, quantitative analytics, or a similarly rigorous technical role

• Strong Python and SQL, plus comfort with APIs, backend systems, and data pipelines

• Proven ability to design, build, and ship reliable systems

• Strong quantitative reasoning applied to real-world problems

• Hands-on experience with machine learning, LLM workflows, model-based automation, or analytical applications

• Ability to work directly with customers and turn ambiguous requirements into clear technical plans

• Strong communication and sound engineering judgment

• Experience with forecasting, optimization, simulation, or scenario-modeling systems

• Experience building evaluation frameworks, control layers, or human-in-the-loop AI workflows

• Familiarity with symbolic systems, rules engines, DSLs, or formal specification

• Prior forward-deployed, solutions, or customer-embedded engineering experience

• Exposure to capital markets, enterprise finance, or other complex operational domains