Navin Sharma

Chief Technology Officer

Distributed Systems ArchitectureCloud-Native EngineeringAI/ML InfrastructurePlatform Engineering

About Navin Sharma

Navin Sharma is the Chief Technology Officer at Halkwinds, responsible for the technical vision, engineering architecture, and platform engineering across the organisation. He brings over 15 years of experience designing and scaling distributed systems, cloud-native platforms, and AI/ML infrastructure for enterprise clients globally.

Navin has architected mission-critical systems across healthcare and fintech verticals — deploying solutions that handle billions of daily transactions with sub-100ms latency. His expertise spans cloud infrastructure on AWS, Azure, and GCP; AI/ML pipeline engineering; and blockchain-based enterprise applications.

He is the principal architect behind several of Halkwinds' proprietary platforms and has co-authored research on cloud cost optimisation and AI infrastructure patterns. Navin mentors engineering teams across Halkwinds' global offices and represents the company at technical forums including AWS re:Invent and Google Cloud Next.

Published Work

Research Contributions

Cloud Cost Audit Framework — Principal Author
Enterprise AI Adoption Trends 2026 — Technical Reviewer
AI Infrastructure Patterns for High-Scale Systems — Author

Areas of Expertise

Distributed Systems ArchitectureCloud-Native EngineeringAI/ML InfrastructurePlatform EngineeringDevOps & Site ReliabilityBlockchain Architecture

Technologies

AWSAzureGoogle CloudKubernetesTerraformPyTorchTensorFlowApache KafkaDatabricksSnowflake

Experience

15+years of industry experience

Industries Served

Healthcare ITFinancial TechnologyE-CommerceiGaming

Hayward, CA, USA

Related Services

All Authors at Halkwinds

Navin's Research Areas

Relevant Research & Benchmarks

View all research →

Enterprise AI24 min

Enterprise AI Adoption Trends 2026

Enterprise AI has crossed the operational threshold. Seventy-two percent of Fortune 500 organizations now run at least one AI system in production — and the average enterprise manages 3.4 concurrent AI initiatives. This report maps the state of enterprise AI across healthcare, manufacturing, financial services, retail, and beyond.

Read report

Healthcare AI22 min

Healthcare AI Trends 2026

Healthcare AI is the fastest-growing sector in enterprise AI investment, projected to grow from $45.2B (2025) to $187.4B by 2030. This report examines clinical AI maturity, administrative automation ROI, and the emerging regulatory frameworks that will define healthcare AI deployment strategy through 2028.

Read report

SaaS Engineering19 min

SaaS Development Benchmarks 2026

What does it actually cost to build and scale a SaaS product in 2026? This report benchmarks engineering team size, deployment frequency, infrastructure spend, and time-to-market across 521 SaaS companies — from $1M ARR seed-stage startups to $100M+ enterprise SaaS leaders.

Read report

AI Agents21 min

AI Agent Adoption Report 2026

AI agents are the most transformative enterprise technology category of the 2025–2026 cycle. This dedicated report examines architecture patterns, deployment economics, governance approaches, and the emerging multi-agent production landscape across 634 organizations — the most comprehensive agent-specific enterprise research available.

Read report

View all research →

Implementation Cost Guides