What the role involves
About Us
Nanonets is transforming the way businesses work. Our AI platform takes the manual, messy, time consuming work — that bog down industries like finance, healthcare, supply chain, and more — and turns them into seamless, automated processes. What once took hours of human effort now takes seconds with Nanonets. Our client footprint spans across 34% of Fortune 500 enabling businesses across various industries to unlock the potential of AI in automating their business processes.
More than 10,000 businesses trust Nanonets because we don’t just promise efficiency — we deliver it with unmatched accuracy, seamless integrations.
In 2024, we raised a $29M Series B led by Accel with continued backing from Elevation Capital and YCombinator, fueling our mission to reshape entire industries through intelligent automation. With revenues tripling year over year and a rapidly scaling global team, we’re not just imagining the future of work — we’re building it.
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The Role
We’re hiring a Technical Engagement Manager to own the post‑sale customer journey and ensure customers achieve meaningful business outcomes with Nanonets. This role sits at the intersection of customers, product, and engineering — blending stakeholder management, light technical fluency, and project leadership.
This is not a pure Customer Success or Account Management role — this position requires hands-on delivery ownership and technical fluency.
You will be the primary point of contact for customers after implementation, responsible for driving adoption, managing expectations, and representing the customer’s voice internally.
Roles and Responsibilities
Customer Engagement & Ownership
- Own customer relationships post‑implementation and serve as the single point of contact for ongoing engagement.
- Build trusted relationships with customer stakeholders across technical and non‑technical teams.
- Proactively manage customer expectations, risks, and escalations to ensure long‑term satisfaction and retention.
Project & Delivery Management
- Translate customer requirements into clear documentation (PRDs, workflows, success criteria) for internal teams.
- Partner closely with Product, Engineering, and Solutions teams to scope work, prioritize requests, and deliver against timelines.
- Maintain and prioritize backlogs across multiple customer accounts.
- Plan and communicate project timelines using structured documentation (project plans, trackers, presentations).
- Ensure end‑to‑end testing and validation of workflows before customer release.
Customer Advocacy & Product Feedback
- Act as the voice of the customer internally, clearly surfacing feedback, enhancement requests, and recurring themes.
- Identify opportunities to improve product adoption, workflow efficiency, and customer outcomes.
- Support renewals and expansions by demonstrating value realization and impact.
Requirements and Skills
- 3+ years of experience in stakeholder‑facing roles such as Technical Engagement Manager, Implementation Manager, Technical Account Manager, Solutions Consultant, or Customer Delivery Manager.
- Bachelor’s degree in Computer Science, Engineering, or a related technical field OR prior experience working as a software engineer or in a technical development role.
- Demonstrated experience leading end-to-end SaaS implementations in partnership with engineering teams.
- Strong technical fluency — comfortable discussing APIs, integrations, data workflows, and system constraints (no coding required).
- Experience translating business requirements into structured technical documentation (PRDs, specs, workflows).
- Proven ability to manage multiple complex customer implementations simultaneously.
- Strong stakeholder management skills with both technical and non-technical audiences.
Nice to Have
- Experience in AI/ML, workflow automation, document processing, or enterprise SaaS.
- Experience working with enterprise or mid-market customers in production environments.
- Prior
About NanoNets
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.
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