Kadamb Goswami: In this conversation, Kadamb traces a personal and professional journey shaped by resourcefulness, resilience, and a relentless focus on building things that tangibly help people. Growing up in a small Indian town, he watched his father—an educator—create low-resource systems so students could learn better. That early example of “impact through intent” led Kadamb to build a simple library tool in college and even assemble his own PC, seeding a lifelong bias for practical problem-solving.

His first big break came at Microsoft India after a rigorous entry exam. Two years later, he transferred to Redmond—motivated by the need to access specialized medical care for his son. At Microsoft he internalized ecosystem thinking: when millions rely on your software, simplicity and customer empathy aren’t nice-to-haves—they’re table stakes.

Curiosity then pulled him to SAP, where he learned to translate complex, enterprise B2B needs into clearer, usable experiences and to connect software decisions to business outcomes. At Amazon, he sought to test those skills at scale inside a framework- and mechanism-driven culture. There, his team focuses on AI-powered finance automation—streamlining accounting booking lifecycles and reconciliation across large organizations.

A pivotal “no” from leadership—rejecting his early pitch for an AI reconciliation platform due to risk—became a defining lesson. Kadamb reframed the vision around trust and extensibility, ran targeted POCs, gathered evidence, and introduced phased pilots and guardrails. That rejection ultimately catalyzed a CXO-level initiative that scaled globally and even led to a patent filing. His takeaway: rejection is early feedback, not failure—use it to refine the story, strengthen data, and deepen customer trust.

On AI in finance, Kadamb emphasizes determinism, auditability, and human-in-the-loop design to minimize hallucinations and earn stakeholder confidence. Trust, privacy, latency, and safety are product features, not afterthoughts. He argues that purpose-driven leadership—ensuring teams understand the “why,” not just the “what”—unlocks better collaboration across product, engineering, and stakeholders, especially when users are many layers away.

Mentorship also plays a central role. The best mentors didn’t hand him answers; they asked sharp questions that revealed blind spots and built conviction. He cautions against “anti-mentors” who lead through fear or control; choose guides who model empathy, clarity, and trust.

Looking ahead, Kadamb wants his career to stand for human-centered intelligence: enterprise AI that is transparent, explainable, ethical, and genuinely useful. Beyond work, he mentors high-school students—coaching accountability, teamwork, and the idea that learning (not grades) is the portable skill that compounds.

The episode closes with a call to embrace adaptability, continuous learning, and community: you don’t need a Big Tech badge to contribute. Start where you are, build responsibly with agents and AI, and keep the human at the center.

About Kadamb Goswami:

- https://www.linkedin.com/in/kadambg/

About Federico Ramallo ✨👨‍💻🌎

🚀 Software Engineering Manager | 🛠 Founder of DensityLabs.io & PreVetted.ai | 🤝 Connecting 🇺🇸 U.S. teams with top nearshore 🌎 LATAM engineers

- 💼 https://www.linkedin.com/in/framallo/

- 🌐 https://densitylabs.io

- ✅ https://prevetted.ai

🎙 PreVetted Podcast 🎧📡

- 🎯 https://prevetted.ai/podcast

- 🐦 https://x.com/PrevettedPod

- 🔗 https://www.linkedin.com/company/prevetted-podcast

00:00 Introduction to Kadamb Goswami

01:05 Early Influences and Problem Solving

03:34 The Importance of Adaptability and Learning

05:08 First Break in Tech and the Role of Luck

10:41 Career Moves and Personal Motivations

13:54 Navigating Company Cultures

17:08 Purpose-Driven Leadership and Team Dynamics

19:00 Learning from Rejection

24:53 Mentorship and Anti-Mentorship

30:42 Future Aspirations and Human-Centered Intelligence