goodfin

About Goodfin Goodfin is an AI-native wealth platform focused on private markets. We’re building intelligent, agentic systems that help accredited investors research, evaluate, and act on private investment opportunities with clarity and confidence. This is not an AI “feature.” AI is the product. As a Staff AI Engineer, you’ll be a technical leader responsible for designing, building, and hardening the core intelligence systems behind Goodfin—systems used by real investors making real financial decisions. This is a hands-on role for someone who wants to work at the boundary of what’s reliable in applied AI—and make it production-grade. You’ll own end-to-end systems: from architecture and modeling decisions through deployment, evaluation, and iteration. You’ll also help define technical standards and shape how we build AI as a company. What You’ll Work On Architecting LLM-powered, agentic systems for private market research, analysis, and decision support Designing hybrid reasoning pipelines that combine LLMs with retrieval, structured financial data, rules, and tools Building robust RAG pipelines over unstructured, noisy, and proprietary data (PPMs, decks, filings, internal memos) Developing evaluation frameworks for reasoning quality, faithfulness, latency, and cost Implementing observability, debugging, and failure-handling for multi-step AI workflows Partnering closely with business and design to translate ambiguous user needs into reliable intelligent behavior Raising the bar on AI engineering practices across the team through example and mentorship **Concrete Example **Build an AI deep research analyst that can synthesize deal documents, market data, news articles, and comparable deals into actionable, well-sourced insights—while surfacing nuances rather than hiding it. Why This Is Hard Product intuition matters: We’re building a sticky, high-value product for real investors—not a demo or internal research tool. High-stakes domain: Private market investing requires accuracy, explainability, and calibrated uncertainty. “Mostly right” is not acceptable. Data complexity: There is no clean source of truth. Data is fragmented, sparse, and often contradictory. Reasoning over generation: The challenge is building systems that reason, compare tradeoffs, and surface uncertainty—not just generate fluent text. Agent reliability: Multi-step, tool-using agents must behave consistently in production, not just in demos. Evaluation is unsolved: You’ll help define what “good” looks like when traditional ML metrics fall short. Trust as a system property: Explainability, sourcing, and failure modes are core technical requirements—not UX afterthoughts. What We’re Looking For 6+ years of software engineering experience, with deep hands-on work in applied AI / ML systems Strong fundamentals in Python and backend system design Proven experience with LLMs (prompting, fine-tuning, RAG, agentic workflows, or evaluation tooling) Experience owning ambiguous, high-impact systems from concept to production Comfort making architectural tradeoffs under real-world constraints Ability to think at the system level while still shipping high-quality code High product intuition and a strong sense of responsibility for user outcomes Bonus Experience in fintech, data-intensive products, or regulated environments How We Work Small, lean team with high ownership and minimal bureaucracy Direct access to users and fast feedback loops Strong bias toward clarity, correctness, and speed High standards for technical rigor where trust matters What Success Looks Like AI systems that customers trust and rely on—not just experiment with Measurable improvements in reasoning quality, reliability, and latency Clear architectural patterns that scale with product complexity A higher technical bar across the team through example and mentorship Why Join Work on real, unsolved AI engineering problems in production Develop systems used for real financial decision

About Goodfin Goodfin is an AI-native investment platform for private markets. We’re building agentic AI systems that help investors research, evaluate, and act on private investment opportunities with clarity and confidence. The Role We’re looking for experienced wealth and investment advisors to work with us to help shape the intelligence behind Goodfin’s AI products. This is not a client-facing advisory role and not a sales role. Instead, you’ll act as a domain expert — contributing your judgment, frameworks, and decision-making process to help train, evaluate, and refine how our AI thinks and behaves. What You’ll Do Provide input on investment analysis frameworks, diligence processes, and decision criteria Review and test AI-generated analyses for accuracy, completeness, and practical usefulness Help calibrate AI outputs around risk, uncertainty, and suitability Identify gaps, edge cases, and failure modes in AI reasoning Participate in structured product reviews, testing sessions, and feedback loops Collaborate with engineering and product teams to translate human judgment into system behavior What We’re Looking For 4+ years of experience as a wealth advisor, investment advisor, portfolio manager, or allocator Deep familiarity with private markets (pre-IPO, growth equity, venture, private credit, or alternatives) Strong analytical judgment and ability to explain how and why decisions are made Comfort working with early-stage products and giving candid feedback Interest in how AI can responsibly augment human expertise Bonus: CFA, CFP, CAIA, or similar credentials How This Engagement Works Flexible, part-time consulting arrangement Project-based or retainer-based (depending on fit) Regular collaboration with Goodfin’s product and AI teams No obligation to bring clients or sell product Why This Is Interesting Direct influence on how AI is applied to real investment decisions Opportunity to shape the future of advisor-grade AI tools Intellectual partnership with a senior, product-driven team Early visibility into cutting-edge AI systems for private markets (and beyond — we will be launching other wealth products in 2026) If you care about the quality of investment decision-making — and want to help shape the tools that will define the next generation of wealth platforms — we’d love to talk.

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.