Applied AI Engineer

About Greenboard

At Greenboard, we’re building the future of financial compliance. Greenboard is the unified, AI-native compliance operating system for RIAs, fintechs, private funds, hedge funds, and more. It replaces the fragmented mix of legacy tools and automates more than previously possible. By centralizing data and workflows, Greenboard helps firms reduce regulatory risk, simplify their technology stack, modernize how they run compliance, and save money.

Our founding team includes engineers who have scaled products at Amazon, Google, and multiple unicorn startups. We’re backed by Y Combinator, General Catalyst, Base10, and other top-tier investors, and have raised over $20M to date. Brand-name financial institutions already rely on Greenboard — and we’re growing fast.

About the Role

We're looking for an Applied AI Engineer to define and build the core AI systems powering Greenboard.

This is an AI-first engineering role. You’ll work on model integration, agent behavior, and system design — while also owning how those capabilities translate into real product experiences.

You’ll operate end-to-end: from designing how models should behave, to building the systems that support them, to shaping the user experience that makes them useful in a high-stakes, regulated environment.

We’re a team that values truth-seeking, creativity, and strong opinions loosely held. We enjoy spirited debate, exploring unconventional ideas, and ultimately shipping.

This is a full-time, on-site role in NYC.

What You'll Do

Core AI Systems

• Design and implement systems around LLMs and related models, including tool use, retrieval, memory, and orchestration

• Own how models interact with internal systems and external data to produce reliable, grounded outputs

Agent Behavior & Model Quality

• Develop and iterate on prompts, routing strategies, and context assembly to improve accuracy and usefulness

• Define how the system chooses tools, retrieves information, and generates responses aligned with user intent and firm policy

• Continuously improve system behavior so each release measurably increases quality and trust

Evaluation, Observability & Reliability

• Build evaluation frameworks to measure performance and detect regressions

• Improve observability into model behavior and system outputs

• Treat “wrong with confidence” as the primary failure mode — and design systems to minimize it

Product Integration

• Translate AI capabilities into intuitive product experiences

• Work across the stack to ensure tight integration between model behavior and user-facing features

Systems & Automation

• Build pipelines that connect model outputs to sources of truth across the platform

• Automate workflows by leveraging deep integrations with Greenboard’s underlying system of record

Cross-Functional Collaboration

• Partner with engineering, product, and domain experts to define problems and validate solutions

• Work closely with customer-facing teams to ensure the system performs in real-world scenarios

What We're Looking For

• Strong experience working with LLMs or similar models — including prompt design, evaluation, and iteration

• Experience with Typescript and building AI/ML powered systems in production

• Ability to design systems around models (tooling, retrieval, orchestration), not just call APIs

• Strong engineering fundamentals — comfortable building backend systems and APIs (frontend experience a plus)

• Strong product instincts — you care about how systems behave in real user workflows

• Ability to reason about tradeoffs between accuracy, latency, and cost

• Clear communicator who can collaborate across technical and non-technical teams

Nice to Have

• Experience building agent-based systems, copilots, or AI-native products

• Familiarity with retrieval-augmented generation (RAG), tool use, and evaluation frameworks

• Experience working with structured data systems and building integrations across complex products

• Background in fintech or other regulated industries

Benefits

• Salary range: $170,000–$280,000 + meaningful equity

• 401(k) with 5% company match

• Medical, dental, and vision coverage

• 15 days PTO + 11 company holidays + flexible sick time

• 2 additional PTO days for each year of service (up to 10 additional days)

• 10 remote days per year plus additional around the holidays

• Bi-annual off-sites and team retreats

• Front-row seat to building the operating backbone of modern finance