The Pragmatic Engineer
From Software Engineer to AI Engineer – with Janvi Kalra
· Summarized
Key takeaways
- Proactively seek opportunities and prepare for internships through mentorship, networking, and comprehensive preparation.
- Evaluate different types of tech companies (product, infrastructure, model) to align career goals with personal interests.
- Transitioning into AI engineering requires continuous self-learning, hands-on projects, and a willingness to innovate.
- A strong company culture, exemplified by OpenAI, enables engineers to work quickly and effectively while fostering collaboration.
- AI tools can enhance productivity for engineers but foundational coding skills and a deep understanding remain essential.
Summary
Breaking into Tech and the Journey of Janvi Kalra
In this episode, Janvi Kalra shares her inspiring journey from a university student to landing internships at top tech companies, including Google and Microsoft. She discusses the proactive steps she took to secure these opportunities, such as writing compelling essays and preparing for interviews with resources like 'Cracking the Coding Interview' and valuable mentorship coffee chats. Janvi highlights the importance of having clear preferences and setting goals when entering the tech field.
Navigating Internships and Choosing a Career Path
Janvi reflects on her internship experiences, emphasizing the contrasts between working at large tech companies versus startups. She found that working in startups offered her diverse experiences and quicker learning opportunities. Despite being told 'no' initially when trying to join CODA’s AI team, she remained persistent and eventually secured a position there, showcasing the importance of resilience and passion in pursuing one's career goals.
Evaluating AI Companies for Success
Janvi outlines a framework for assessing AI companies, categorizing them into product, infrastructure, and model companies. She emphasizes the necessity to evaluate the growth potential of companies based on factors such as revenue growth, customer loyalty, and the competitive landscape. The discussion gives insights into what characteristics indicate a viable startup and the importance of doing thorough due diligence before joining the company.
Transitioning to AI Engineering
Janvi delves into her transition from software engineer to AI engineer, detailing her self-learning journey through hackathons and personal projects. She discusses the skills necessary for an AI engineer, such as understanding LLMs, prompt engineering, and the value of embracing experimentation. The chat highlights how AI engineering is less about rote tasks and more about creativity and problem-solving.
The Culture and Processes at OpenAI
Janvi shares her current role at OpenAI, focusing on the team's commitment to building safe AI technologies. She describes the unique aspects of working at OpenAI—fast-paced iterations, open communication, and the collaborative culture that encourages proactive contributions. The discussion also covers the growing responsibilities of AI engineers and the necessary balance of trusting engineers while handling the complexities of AI systems.
Impact of AI on Software Engineering for New Graduates
In the concluding discussion, Janvi reflects on the potential impact of AI tools on young engineers entering the field. She argues that while AI tools might change how coding is approached, foundational skills such as system understanding and debugging remain crucial. She encourages new graduates to leverage AI for learning while also emphasizing the importance of deep understanding and personal initiative in their careers.
Sponsors
- Statsig · The unified platform for flags, analytics, experiments, and more.
- Sinch · Connect with customers at every step of their journey.
- Cortex · Your Portal to Engineering Excellence.
Show notes
Supported by Our Partners
• Statsig — The unified platform for flags, analytics, experiments, and more.
• Sinch — Connect with customers at every step of their journey.
• Cortex — Your Portal to Engineering Excellence.
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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!
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Timestamps
(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
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The Pragmatic Engineer deepdives relevant for this episode:
• AI Engineering in the real world
• Building, launching, and scaling ChatGPT Images
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See the transcript and other references from the episode at https://newsletter.pragmaticengineer.com/podcast
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