About Goodfin
Goodfin is an AI-native investment platform giving accredited investors access to pre-IPO and alternative assets — with intelligent systems that don’t just surface data, but
reason, act, and iterate.
We’re building agentic AI that can analyze complex financial inputs, orchestrate multi-step workflows, and continuously improve through feedback. This is not a research lab or a slow enterprise environment. We move fast, ship constantly, and expect engineers to think like builders
and product owners.
Role Overview
As an
AI Engineer, you’ll help build and ship
agentic AI systems that sit at the core of the Goodfin product. You won’t be handed perfectly scoped tickets — you’ll help define
what should be built,
how it should behave, and
why it matters to users.
This Role Is For Engineers Who
- Care deeply about product outcomes, not just models
- Take ownership end-to-end
- Thrive in high-expectation, high-autonomy environments
- Want to work on AI systems that actually run in production and make decisions.
You’ll work closely with our entire team, but you’re expected to operate independently, move fast, and push ideas forward.
You’ll be a key contributor to building robust AI systems, RAG workflows, and scalable backend services that make Goodfin’s intelligent features reliable and impactful in real-world settings.
What You’ll Do
- Build and iterate on agentic AI workflows that reason across data, tools, and actions.
- Design and implement LLM-powered systems that go beyond single prompts (multi-step planning, tool use, memory, feedback loops).
- Ship production-grade AI features — not demos — that real users rely on.
- Own meaningful parts of the product lifecycle: idea → design → build → launch → iterate.
- Partner directly with product and design to shape how AI features behave in the real world.
- Implement and improve RAG pipelines, evaluations, and reliability mechanisms.
- Monitor live AI systems, debug failures, and continuously raise quality.
- Move quickly with imperfect information — making good tradeoffs instead of waiting for perfect specs.
- Stay current with recent AI/ML tools and frameworks — particularly around LLM ecosystems and agent frameworks.
Who You Are
Required Qualifications
- 3 or more years of professional experience in software or AI engineering.
- Strong hands-on coding experience in Python and backend systems.
- Practical familiarity with modern AI/ML tools — working with LLM APIs (e.g., OpenAI, Claude) and ML libraries.
- Experience integrating models or AI systems into production applications.
- Experience with vector stores, indexing, or retrieval systems.
- Familiarity with frameworks like LangChain, AutoGen, or similar agent tools.
- Exposure to cloud environments (AWS, GCP) and CI/CD pipelines.
- Comfortable writing maintainable, scalable code and collaborating with backend and full-stack engineers.
- Strong communication skills and team mindset.
Preferred (Nice-to-Have)
- Experience with evaluation tooling or building quality metrics for generative systems.
- Enjoy writing or creating content around AI and what we are building at Goodfin.
- Love for consumer or investing apps.
- Previous experience working at a fintech or in another regulated domain.
Why Join Goodfin
- Work on real AI engineering problems — not research prototypes — that impact a live fintech product.
- Build with a small, mission-driven team with direct access to founders.
- Competitive compensation with significant equity participation in a fast-growing early-stage startup.
