Unsiloed AI

About Unsiloed Unsiloed is building the infrastructure layer for unstructured enterprise data. We are backed by Y Combinator and a group of well-known investors and operators from the Valley. A huge amount of enterprise work still runs on documents that machines cannot read well. Loan files, broker statements, insurance claims, medical records, contracts, and financial reports. Teams pay people to read them, copy values into systems, reconcile mistakes, and chase exceptions. AI applications built on top of these documents inherit the same problems: hallucinated fields, missed line items, broken tables, and low confidence the moment anything goes into production.    Unsiloed turns these documents into structured, production-grade outputs that AI systems and operational teams can actually build on. The right field, in the right schema, with the right confidence signals, at a quality customers are comfortable putting in front of their own end users. We are already in production with customers across financial services, legal, insurance, and healthcare. Some are using us to replace manual operations work that used to take entire teams. Others are building net-new AI products on top of us and taking them to market themselves. Every deal so far has been founder-led, and the next step is turning that into a repeatable go-to-market motion. On deployment, we run as a managed API, inside private VPCs, and fully on-prem for customers that require it. Our customer base sits in regulated industries with real compliance bars, and we are built for teams that care deeply about security, reliability, and deployment flexibility. What you will do Work alongside the founders on the GTM motion end to end Outbound, inbound qualification, discovery calls, POCs, pricing conversations, procurement, and closing early customers. Help refine and operationalize what is already working Improve messaging, outbound sequences, qualification criteria, POC structure, pricing approaches, and customer workflows as we learn more about the market. Run and evaluate GTM experiments Outbound email, founder-led content, partnerships, communities, events, and other distribution channels. Help us figure out which motions consistently generate high-quality pipelines for a technical infrastructure product like ours. Get close to customers and the product You will sit in on customer calls, understand where the product is resonating or breaking down, and feed those learnings back into product, positioning, and sales strategy. Help define the commercial foundation of the company This is a highly collaborative role with significant influence on how we position the company, define the ICP, shape the sales process, and build the early GTM culture. Over time, help scale the function As the motion becomes more repeatable, you will help us think through how to grow the team across sales, outbound, partnerships, solutions engineering, and related functions. What success looks like In the first 3 months Work closely with the founders on active deals and pipeline generation Develop a strong understanding of the ICP and buyer pain points Run technical POCs with customers Contribute to building a more repeatable founder-assisted sales process In 6-12 months Consistent pipeline generation outside founder networks Clear understanding of which verticals and motions convert best Repeatable POC and qualification process Improved sales velocity and conversion rates Early foundation for scaling the GTM organization Compensation The base pay range for this role is $120k – $200k per year.

We are hiring a Founding Software Engineer in San Francisco. We are building a small, talent-dense team. This role will define the engineering archetype at Unsiloed AI and set the ceiling for the team. We strongly believe technical DNA compounds (or degrades) with every hire and hence the first few matter disproportionately. You will be expected to operate proactively, take full ownership, and independently drive systems from idea to production. What you Will Do As a Founding Software Engineer, you will own the entire technical stack end-to-end, from core infrastructure and production systems to deployment, reliability, and developer experience. Architect, build, and scale core backend systems powering document intelligence and VLM-based workflows Own production infrastructure end-to-end: deployments, monitoring, performance, reliability Design and operate high-throughput, low-latency services in real production environments Take systems from R&D → production → enterprise scale Build and maintain cloud and on-prem deployments (Docker, Kubernetes, Helm) for enterprise customers Establish best practices for CI/CD, observability, debugging, and incident response Work closely with the founders and research team to turn research prototypes into production-grade, scalable systems. What We are Looking For This role is backend & infrastructure-heavy. You should have most of the following: Experience building and operating scaled production systems Strong backend engineering skills (Python required; C++/Rust is a major plus) Experience with distributed systems (microservices, parallel processing, queues, caches like Redis) Deep familiarity with cloud infrastructure (AWS, GCP, Azure) Hands-on experience with Docker, Kubernetes, Helm, and infrastructure-as-code (Terraform / Pulumi) An ownership mindset Nice to have: Experience serving ML / VLM / GPU-heavy workloads Compensation: $150k – $300k Equity: 0.1% – 1% Location: In-person, San Francisco Visa: Open to sponsoring Hiring process: We don’t believe interviews alone can assess fit on either side. Our process centers around paid work trials, which can be done remotely. You will work with us on real problems, collaborate as peers, and get a genuine sense of what building Unsiloed AI feels like. For any questions, email hiring [at] unsiloed [dot] ai

We are hiring a Founding ML Researcher in San Francisco. We are building a small, talent-dense team. This role will define the engineering archetype at Unsiloed AI and set the ceiling for the team. We strongly believe technical DNA compounds (or degrades) with every hire and hence the first few matter disproportionately. You will be expected to operate proactively, take full ownership, and independently drive systems from idea to production. What you Will Do As a Founding ML Researcher, you will shape the company’s ML research direction and translate research into production-ready document AI models. Own the end-to-end ML lifecycle:  research → experimentation → training → evaluation → production deployment  Work with engineering team to transition research into deployed, scalable systems Drive best practices for data, experimentation, evaluation, and model iteration. What We are Looking For This role is research-heavy but product-oriented. You should be comfortable moving between theory, experimentation, and real-world deployment. You should have experience with most of the following: Training and deploying state-of-the-art models for parsing and understanding unstructured data Experimenting with novel techniques to improve layout models and VLM-based document understanding Building data pipelines, evaluating model performance, and integrating models into production systems Working directly with the founders to shape the product direction and engineering strategy Bonus if you have PhD or equivalent research experience in VLM, Computer Vision or related areas. Publications in top-tier AI conferences   Familiarity with model serving, inference optimization, or deployment at scale For any questions, email hiring [at] unsiloed [dot] ai