Nanonets is a SAAS product that automates manual processes for other companies. We use state-of-the-art machine learning algorithms to enable this hyper-automation.

We are looking for our first Sales Engineer to work closely with our sales team (In US timezone) and assist them in selling this technical product to other companies. A big part of the role will be to understand Nanonets product really well, understand customer requirements/goals and build machine learning models on the Nanonets platform to demo capabilities to customers on their own data. This would be instrumental in helping close sales faster.

If you are interested in AI/ML space, good with communication, enjoy tasks with quick wins and love solving on diverse set of problems, this role would be good fit for you.

Responsibilities:

Accompanying salespeople on client calls to answer technical questions, understand their current processes and goals with Nanonets, and suggest improvements.
Building solutions/demos based on their requirements using Nanonets product
Solving challenges potential customers might be facing with the product
Researching about customers current tools/stack and building technical architecture for end solution we are proposing that will solve their problem

What You'll Bring to the Table (Must-Haves):

Proficiency in Python for scripting or building solutions
Experience working with relational databases (any major DB works)
Understanding of APIs and how they integrate with products
Comfort using Git for version control and collaboration

AI agents break where it matters most: when the details are buried in an invoice, a BoL, or a clinical document. Most agents guess. They hallucinate field values, apply rules inconsistently, and when something goes wrong, you can’t tell why or fix it without redoing the work yourself.

Nanonets is built differently. Every extraction is traceable. You can see exactly what the agent read, what rule it applied, and why it made the call it did. When it’s uncertain, it flags the right thing for human review instead of silently getting it wrong. When you correct it, it learns. When you add business rules, it tracks which rule drove which decision.

Anyone can build agentic workflows, but AI agents are black boxes that struggle with complex files and processes, like POs, invoices, BoLs and clinical documents. Nanonets agents understand key details in files, work through complex processes and act with transparency, making them the most reliable foundation for building workflows where details matter.

Nanonets reduces processing time by 95% by automating messy manual processes and delivering clean data to systems of record like SAP, SFDC and more. That’s why Nanonets is the automation layer global enterprises reach for when accuracy is non-negotiable.

Sales Engineer

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