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, fintech, and manufacturing 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 TechnologyManufacturingE-CommerceiGaming

Hayward, CA, USA

Related Services

Related Case Studies

All Authors at Halkwinds

Navin's Research Areas

Relevant Research & Benchmarks

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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.

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Healthcare AI20 min

Healthcare AI Adoption Trends 2026

Healthcare AI has moved decisively past the proof-of-concept era. In 2026, the defining question for health system leadership is no longer whether AI delivers value in clinical and operational contexts — that question has been answered affirmatively across enough high-quality deployments to be settled — but rather how to scale individual successes into enterprise-wide capabilities without accumula...

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Healthcare AI18 min

The Future of Digital Health Platforms

Digital health platforms are undergoing a structural transformation that will define how enterprise health systems operate for the next decade. The shift is not simply one of technology modernization — it represents a fundamental reordering of clinical workflow architecture, data governance responsibilities, and vendor relationships. Health systems that approach this moment with a coherent platfor...

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Healthcare AI19 min

Medical AI Market Analysis 2026

The medical AI market in 2026 is no longer a market of early pilots and proof-of-concept demonstrations. Across diagnostic imaging, clinical decision support, administrative automation, patient engagement, and drug discovery, AI systems are operating in production clinical and operational environments at scale. The strategic question facing health system executives, digital health investors, and t...

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Implementation Cost Guides