Priyanka Jindal

Priyanka Jindal

Operator & Engineer

As an experienced operator and engineer, I find joy in applying technology to solve real business problems. I believe that the most impactful work happens only when the trio of talent, technology, and business come together - when any one is missing, it leads to sub-optimal outcomes.

I am currently spending time building AI Agents, and diving into the challenges of architecting Coding and Software Engineering Agents, a domain I find deeply impactful.

I have a proven track record leading product management, software engineering, and enterprise GTM teams to build and scale managed cloud infrastructure services at Amazon Web Services (AWS) and developer tools at a Sequoia backed startup, all while based in San Francisco. During my time at AWS, I led the inference workloads roadmap for EC2 app networking ($1b+ ARR portfolio), built & scaled two new 0-1 products to grow VPC Networking and IoT platforms ($200M+ ARR portfolio), directly served and engaged tens of Fortune 500 strategic customers, operated services with tens of thousands of mid-market and enterprise customers, and designed a data governance program for all Alexa wearables. I have deep expertise in technical product management and scaling enterprise GTM, specifically hybrid-cloud deployment model, usage-based pricing & packaging, and developing channel partnerships. Before finding my way back to my engineering roots, I started my career as a quant developing algorithms and pricing at Nomura Securities and Lehman Brothers in Tokyo.

I earned my bachelors in Computer Science and Engineering from Indian Institute of Technology Delhi, where I received the outstanding research award for my undergraduate thesis (built an FPGA accelerator to speed up a compute intensive application by 5x). To navigate across countries (Japan to USA), industries (quant trading to high-tech), function (finance to product development) and US immigration system, I also earned an MBA from Kellogg School of Management, Northwestern University.

Blog Posts

Building an AI Agent business case

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Pitfalls of AI <persona> positioning

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Divinely discontent with AI

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My AI native dev environment

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What has not changed with Enterprise AI?

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Self-host models or use APIs?

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