Entrepreneur In Residence

Nanonets is automating document information extraction using AI. We are headquartered in San Francisco. We are backed by prestigious investors from bay area like Y-Combinator, SV Angels, Sound Ventures by Ashton Kutcher. We are currently profitable and growing at a fast pace and looking to expand our team. We are building a product that lets companies automate extracting key information from documents like invoices, receipts, or any other kind of document and integrate it into their workflows saving manual work. We need to keep building features that will let users automate millions of documents of different kinds every day, feed them to our AI for learning, plug our API to external systems like salesforce, quickbooks, RPA providers etc. You should check it out at https://app.nanonets.com About Nanonets At Nanonets, we’re building the future of document intelligence. Our platform helps thousands of companies automate workflows that rely on messy, unstructured data—think invoices, PDFs, emails, websites, support tickets—using cutting-edge AI. We’re growing fast and backed by top investors. Now, we’re looking to build entirely new business lines. That’s where you come in. What You’ll Do This is not your typical role. You’ll be given white space, resources, and a mandate: Identify a high-potential vertical. Validate it. Build it. Own it. Expect to: Identify and validate new GTM opportunities through user research, cold outreach, and experimentation. Own the full sales cycle: cold calls, emails, demos, closing. Build deep customer empathy and turn insights into scalable repeatable motions. Work across product, ops, and marketing to spin up MVPs and launch GTM campaigns. Deliver traction: first $1M in pipeline → revenue → team. Be the CEO of your vertical, backed by us. Identify and validate new GTM opportunities through user research, cold outreach, and experimentation. Own the full sales cycle: cold calls, emails, demos, closing. Build deep customer empathy and turn insights into scalable repeatable motions. Work across product, ops, and marketing to spin up MVPs and launch GTM campaigns. Deliver traction: first $1M in pipeline → revenue → team. Be the CEO of your vertical, backed by us. You’d Be a Great Fit If: You’ve founded or co-founded a startup (whether successful or not). You're a scrappy generalist who loves doing “everything and anything.” You’ve closed deals from scratch (cold email → closed contract). You think in terms of systems and scale , but you’re not afraid to start with duct tape. You’re deeply curious, analytical, and driven by building something from zero. You’ve founded or co-founded a startup (whether successful or not). You're a scrappy generalist who loves doing “everything and anything.” You’ve closed deals from scratch (cold email → closed contract). You think in terms of systems and scale , but you’re not afraid to start with duct tape. You’re deeply curious, analytical, and driven by building something from zero. Why Join Nanonets as an EIR? No red tape. We’ll give you real ownership, not corporate innovation theatre. Proven playbooks + resources. We’ve done this before—successfully. Clear path to GM or Founder of New Business Unit. You’ll work closely with the founder/CEO and core team. No red tape. We’ll give you real ownership, not corporate innovation theatre. Proven playbooks + resources. We’ve done this before—successfully. Clear path to GM or Founder of New Business Unit. You’ll work closely with the founder/CEO and core team. Compensation & Benefits: $140,000–$180,000 base salary Equity Flexible hybrid setup from Palo Alto HQ Health, dental, vision $140,000–$180,000 base salary Equity Flexible hybrid setup from Palo Alto HQ Health, dental, vision Some of the interesting things our backend team has shipped Compile python code into C which could be imported into golang and then shipped as binary for on premise systems Autoscale GPU dependent services with kubernetes with a custom metric Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics Building large number and variety of integrations with relatively generic interface like salesforce, quickbooks, RPA's, external databases Process large number of files in highly distributed manner in golang Compile python code into C which could be imported into golang and then shipped as binary for on premise systems Autoscale GPU dependent services with kubernetes with a custom metric Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics Building large number and variety of integrations with relatively generic interface like salesforce, quickbooks, RPA's, external databases Process large number of files in highly distributed manner in golang Some of the interesting things our frontend team has shipped Ability for users to annotate documents so AI can learn which fields to extract Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics Letting users build complex visual workflows around our API in our product. Let users visualize complex ML metrics in a very simple and intuitive way Ability for users to annotate documents so AI can learn which fields to extract Letting users build complex visual workflows around our API in our product. Let users visualize complex ML metrics in a very simple and intuitive way Our stack: Databases Cassandra DB Postgres/MySQL Backend Golang for API and other microservices Python for Machine learning (Tensorflow, Pytorch) Frontend React, Typescript Mobx Cloud Providers AWS GCP for ML heavy workload Monitoring/Alerting ELK for logging Prometheus for Monitoring Graphana for dashboards Orchestration Kubernetes DevOps Jenkins for CI/CD Databases Cassandra DB Postgres/MySQL Cassandra DB Postgres/MySQL Cassandra DB Postgres/MySQL Backend Golang for API and other microservices Python for Machine learning (Tensorflow, Pytorch) Golang for API and other microservices Python for Machine learning (Tensorflow, Pytorch) Golang for API and other microservices Python for Machine learning (Tensorflow, Pytorch) Frontend React, Typescript Mobx React, Typescript Mobx React, Typescript Mobx Cloud Providers AWS GCP for ML heavy workload AWS GCP for ML heavy workload AWS GCP for ML heavy workload Monitoring/Alerting ELK for logging Prometheus for Monitoring Graphana for dashboards ELK for logging Prometheus for Monitoring Graphana for dashboards ELK for logging Prometheus for Monitoring Graphana for dashboards Orchestration Kubernetes Kubernetes DevOps Jenkins for CI/CD Jenkins for CI/CD