AWS SDM / Product intelligence / Engineering leadership / Distributed systems

Praveen Kotteswaran

Engineering leader building AI-powered product intelligence, developer productivity, and distributed decision systems. Software Development Manager at AWS with 15+ years across Amazon and AWS, leading teams that turn customer, product, and operational signals into trusted platforms for better decisions and faster execution.

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Operating Thesis

A people leader with the technical depth to make hard platform calls.

The thread across my career is helping large engineering organizations replace fragmented, expert-driven workflows with durable platforms. I lead teams, planning, architecture, operational readiness, hiring, performance coaching, and cross-org execution while staying close to the product and system decisions that determine whether a platform actually earns trust.

Selected Case Studies

Three examples of leadership, product judgment, and system execution.

01

AWS Console Product Intelligence

From expert-driven analysis to product-decision systems.

Problem AWS teams needed faster ways to understand customer behavior, friction, feedback, and launch impact.

Role Led engineering strategy, roadmap execution, architecture direction, and operational readiness.

Impact 500+ service teams, hundreds of surfaces, and targeted feedback setup reduced from weeks to hours.

02

AI Product Intelligence

Governed natural-language analytics over product signals.

Problem Analytics depended on specialist query knowledge and fragmented feedback tools.

Decision Governed tools, not unbounded chat-over-data.

Impact 5K monthly users, strong query success, low-latency responses, and operational trust.

03

Engineering Productivity

Team knowledge converted into developer leverage.

Problem Engineers lost time on discovery, repeated review feedback, and tribal knowledge.

System Code-review patterns, co-change signals, conventions, and human-reviewed AI drafts.

Impact Target same-day reviewable drafts for recurring code-review patterns.

Scope, Scale & Operating Ownership

12 + 40+ Engineers led direct and workstream-wide

500+ Service teams on the platform

5K Monthly users of governed AI tools

18TB/day Telemetry processed into signal

50% Faster launch validation cycle

Relevant Leadership Areas

AI platforms Product intelligence Developer productivity Distributed systems & telemetry

Technical Range