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What does it take to land a job as an AI Engineer—and thrive in the role? In this episode of Pragmatic Engineer, I’m joined by Janvi Kalra, currently an AI Engineer at OpenAI. Janvi shares how she broke into tech with internships at top companies, landed a full-time software engineering role at Coda, and later taught herself the skills to move into AI Engineering: by things like building projects in her free time, joining hackathons, and ultimately proving herself and earning a spot on Coda’s first AI Engineering team. In our conversation, we dive into the world of AI Engineering and discuss three types of AI companies, how to assess them based on profitability and growth, and practical advice for landing your dream job in the field. We also discuss the following: • How Janvi landed internships at Google and Microsoft, and her tips for interview prepping • A framework for evaluating AI startups • An overview of what an AI Engineer does • A mini curriculum for self-learning AI: practical tools that worked for Janvi • The Coda project that impressed CEO Shishir Mehrotra and sparked Coda Brain • Janvi’s role at OpenAI and how the safety team shapes responsible AI • How OpenAI blends startup speed with big tech scale • Why AI Engineers must be ready to scrap their work and start over • Why today’s engineers need to be product-minded, design-aware, full-stack, and focused on driving business outcomes • And much more! — Brought to you by: • Statsig — The unified platform for flags, analytics, experiments, and more http://statsig.com/pragmatic • Sinch — Connect with customers at every step of their journey https://sinch.com/lander/pragmatic/ • Cortex — Your Portal to Engineering Excellence http://cortex.io/pragmatic — The Pragmatic Engineer deepdives relevant for this episode: • AI Engineering in the real world https://newsletter.pragmaticengineer.... • The AI Engineering stack https://newsletter.pragmaticengineer.... • Building, launching, and scaling ChatGPT Images https://newsletter.pragmaticengineer.... — Where to find Janvi Kalra: • X: https://x.com/janvikalra_ • LinkedIn: / janvi-kalra • Substack: https://janvikalra.substack.com/ Where to find Gergely Orosz: • X: https://x.com/GergelyOrosz • LinkedIn: / gergelyorosz • Bluesky: https://bsky.app/profile/gergely.prag... • Newsletter and blog: https://www.pragmaticengineer.com/ — In this episode, we cover: (00:00) Intro (02:31) How Janvi got her internships at Google and Microsoft (03:35) How Janvi prepared for her coding interviews (07:11) Janvi’s experience interning at Google (08:59) What Janvi worked on at Microsoft (11:35) Why Janvi chose to work for a startup after college (15:00) How Janvi picked Coda (16:58) Janvi’s criteria for picking a startup now (18:20) How Janvi evaluates ‘customer obsession’ (19:12) Fast—an example of the downside of not doing due diligence (21:38) How Janvi made the jump to Coda’s AI team (25:48) What an AI Engineer does (27:30) How Janvi developed her AI Engineering skills through hackathons (30:34) Janvi’s favorite AI project at Coda: Workspace Q&A (37:40) Learnings from interviewing at 46 companies (40:44) Why Janvi decided to get experience working for a model company (43:17) Questions Janvi asks to determine growth and profitability (45:28) How Janvi got an offer at OpenAI, and an overview of the interview process (49:08) What Janvi does at OpenAI (51:01) What makes OpenAI unique (52:30) The shipping process at OpenAI (55:41) Surprising learnings from AI Engineering (57:50) How AI might impact new graduates (1:02:19) The impact of AI tools on coding—what is changing, and what remains the same (1:07:51) Rapid fire round — See the transcript and other references from the episode at https://newsletter.pragmaticengineer.... — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].