AI Deployment Engineer

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. Read about the release here: Article 1 Article 2 The Role We are seeking a technically proficient, business-minded AI Deployment Engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, guiding them through ideation, development, delivery, and scaling to accelerate and maximize the value of what they build on our platform. You will have the opportunity to work on the most novel and creative use cases being built on our API, serving as a critical partner in collecting and delivering high-fidelity product and model feedback internally. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Startups Solutions Architecture Lead. Roles and Responsibilities Partner closely with customers as their technical partner to deploy Nanonets to production , helping them rapidly move from ideation to scale. Provide proactive guidance to maximize business impact and accelerate application development. 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. Requirements and Skills 5+ years of experience as a software engineer, ML engineer or equivalent, ideally in a startup environment; experience as a founder or founding engineer is highly valued. Have passion for startups and a belief in their potential to become future large enterprises. Are proficient in Python, JavaScript, and a strong grasp of AI/LLM best practices. Built and/or delivered prototypes on top of our API platform. Can proactively identify opportunities for maximizing our customers’ business value through leveraging the Nanonets API. Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done. Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. Are an effective, high throughput operator who can drive multiple concurrent projects and prioritize ruthlessly. Additional Information Hybrid role, (twice a week in our Palo Alto office), based in the Bay Area, CA. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $120,000 - $160,0000 per year. This role is also eligible for equity and other benefits. ... (truncated, view full listing at source)