Senior Software Engineer, AI

About Us: Fieldguide is establishing a new state of trust for global commerce and capital markets through automating and streamlining the work of assurance and audit practitioners specifically within cybersecurity, privacy, and ESG (Environmental, Social, Governance). Put simply, we build software for the people who enable trust between businesses. We're based in San Francisco, CA, but built as a remote-first company that enables you to do your best work from anywhere. We're backed by top investors including Bessemer Venture Partners, 8VC, Y Combinator, Floodgate, Elad Gil, Justin Kan, Qasar Younis, Eric Ries, and more. We value diversity - in backgrounds and in experiences. We need people from all backgrounds and walks of life to help build the future of audit and advisory. Fieldguide's team is inclusive, driven, humble and supportive. We are deliberate and self-reflective about the kind of team and culture that we are building, seeking teammates that are not only strong in their own aptitudes but care deeply about supporting each other's growth. As an early stage start-up employee, you'll have the opportunity to build out the future of business trust. We make audit practitioners' lives easier by eliminating up to 50% of their work and giving them better work-life balance. If you share our values and enthusiasm for building a great culture and product, you will find a home at Fieldguide. The following should describe you: You want to join an early stage company: We're young, but we've found strong demand for our products and are growing quickly. We've landed numerous top audit and advisory firms as customers, displaced entrenched legacy technology, and have high demand for product access. You believe that great design and UX are requirements: We bring a user-centered approach to problem solving, focusing deeply on our customers. We're competing with legacy software that was built in the 1990's. These products have extremely low user satisfaction, but are worth billions of dollars just because they're entrenched with so many firms. You're obsessed with data: We have a rich dataset that is ripe for automation and AI. With our data advantage, we can provide our users with intelligent automation, predictions of common workflow patterns, and analytics that will fundamentally change the structure of audits. You greatly value culture: Our goals are lofty, we work very hard, and we want to transform an industry. More importantly, we also work responsibly. We place a premium on building a sustainable, inclusive, high EQ, high feedback, and safe company that celebrates individuals of all backgrounds. Responsibilities: Be an essential technical contributor at a Series B company as it scales. Play a leadership role on the end-to-end development of features, specifically in regards to making architectural decisions and trading off different approaches. Bring a mindset of continuous improvement to your work. You'll be responsible for making our technology and processes better over time. Understand how to optimize for iteration speed while maintaining a high quality bar and technical rigor. You'll have experience with several of the following: 5 years of engineering experience Excitement for product-focused application of ML/AI - this will be a production-focused role Exceptional technical proficiency with at least one programming language, particularly Python or TypeScript Understanding of ML concepts like supervised/unsupervised/self-supervised learning, neural networks and deep learning Understanding of modern ML/AI technologies, including natural language processing (NLP) and LLMs (e.g., GPT-3, open source models, etc.), RAG architectures, and their applications Experience architecting systems and data pipelines that can handle the ingestion, digitalization, storage, and retrieval of document-heavy data sets, including document processing, search, and classification Experience in developing, testing, evaluating and deploying ML models Ability to collaborate on all aspects of product strategy and UX Experience shaping an early stage tech stack and product, and engineering organization Nice to haves: Experience training, fine-tuning, and deploying LLMs Familiarity with ML frameworks and tools such as TensorFlow, PyTorch, Keras, scikit-learn Familiarity with modern web tech stacks consisting of several of the following: TypeScript, React, GraphQL, NodeJS, Hasura, Postgres, Python, and AWS Experience with cloud computing platforms like AWS Experience with DevOps and continuous integration/delivery best practices