<h3><strong>About Goodfin</strong></h3>
<p>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 <em>reason, act, and iterate</em>.</p>
<p>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 <em>and</em> product owners. </p>
<h3><strong>Role Overview</strong></h3>
<p>As an <strong>AI Engineer</strong>, you’ll help build and ship <strong>agentic AI systems</strong> that sit at the core of the Goodfin product. You won’t be handed perfectly scoped tickets — you’ll help define <em>what</em> should be built, <em>how</em> it should behave, and <em>why</em> it matters to users.</p>
<p>This role is for engineers who:</p>
<ul>
<li>Care deeply about <strong>product outcomes</strong>, not just models</li>
<li>Take ownership end-to-end</li>
<li>Thrive in high-expectation, high-autonomy environments</li>
<li>Want to work on AI systems that actually run in production and make decisions.</li>
</ul>
<p>You’ll work closely with our entire team, but you’re expected to operate independently, move fast, and push ideas forward.</p>
<p>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.</p>
<h3><strong>What You’ll Do</strong></h3>
<ul>
<li>Build and iterate on <strong>agentic AI workflows</strong> that reason across data, tools, and actions.</li>
<li>Design and implement <strong>LLM-powered systems</strong> that go beyond single prompts (multi-step planning, tool use, memory, feedback loops).</li>
<li>Ship <strong>production-grade AI features</strong> — not demos — that real users rely on.</li>
<li>Own meaningful parts of the product lifecycle: idea → design → build → launch → iterate.</li>
<li>Partner directly with product and design to shape how AI features behave in the real world.</li>
<li>Implement and improve <strong>RAG pipelines</strong>, evaluations, and reliability mechanisms.</li>
<li>Monitor live AI systems, debug failures, and continuously raise quality.</li>
<li>Move quickly with imperfect information — making good tradeoffs instead of waiting for perfect specs.</li>
<li>Stay current with recent AI/ML tools and frameworks — particularly around LLM ecosystems and agent frameworks. </li>
</ul>
<h3><strong>Who You Are</strong></h3>
<p><strong>Required Qualifications</strong></p>
<ul>
<li>3 or more years of professional experience in software or AI engineering.</li>
<li>Strong hands-on coding experience in Python and backend systems.</li>
<li>Practical familiarity with modern AI/ML tools — working with LLM APIs (e.g., OpenAI, Claude) and ML libraries.</li>
<li>Experience integrating models or AI systems into production applications.</li>
<li>Experience with vector stores, indexing, or retrieval systems.</li>
<li>Familiarity with frameworks like LangChain, AutoGen, or similar agent tools.</li>
<li>Exposure to cloud environments (AWS, GCP) and CI/CD pipelines.</li>
<li>Comfortable writing maintainable, scalable code and collaborating with backend and full-stack engineers.</li>
<li>Strong communication skills and team mindset. </li>
</ul>
<p><strong>Preferred (Nice-to-Have)</strong></p>
<ul>
<li>Experience with evaluation tooling or building quality metrics for generative systems.</li>
<li>Enjoy writing or creating content around AI and what we are building at Goodfin.</li>
<li>Love for consumer or investing apps.</li>
<li>Previous experience working at a fintech or in another regulated domain.</li>
</ul>
<h3><strong>Why Join Goodfin</strong></h3>
<ul>
<li>Work on <strong>real AI engineering problems</strong> — not research prototypes — that impact a live fintech product. </li>
<li>Build with a small, mission-driven team with direct access to founders.</l