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Enterprise AI Architecture & Security

Enterprise AI.
Zero compromise
on security.

Bridging cutting-edge generative AI with enterprise identity and cloud security. Executive-level engineering leadership for high-scale, high-stakes platforms.

Discuss your architecture → View capabilities
23+ Years at Microsoft building enterprise platforms
0 → 1 Led enterprise security platforms from greenfield to v1
3 AI products in the current portfolio
100% Focus on LLMOps, MLOps, Identity and Security

Capabilities

Three flagship ways to work together

Concrete, scalable architecture, hands-on technical leadership, and sharp security judgment for teams that need to move fast without cutting corners.

01 / AI Infrastructure

AI Infrastructure & MLOps

Design and optimize inference pipelines built for reliability and cost efficiency — from RAG architecture to agentic orchestration with Model Context Protocol.

  • RAG pipeline architecture and evaluation
  • Azure / AWS inference stack optimization
  • Agentic system design with MCP
  • LLM cost modeling and observability
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02 / Security

Identity & Cloud Security

Bring enterprise IAM rigor to your AI stack. Machine identity, host attestation, zero trust architecture, and secure boot applied to modern cloud-native systems.

  • Zero trust access model design
  • Machine identity and host attestation
  • AI workload security review
  • Secrets management and mTLS architecture
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03 / Leadership

Fractional Technical Leadership

Senior technical leadership for companies that need architectural direction, execution pressure, and trusted judgment without a full-time executive hire.

  • Architecture and roadmap reviews
  • Engineering team structure and hiring
  • Technical due diligence (M&A / VC)
  • Hands-on system design workshops
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About

Enterprise-grade rigor. Founder-level urgency.

Portrait of Naveen Madan

Naveen Madan spent more than 23 years at Microsoft, where he led engineering across Defender, identity, access management, and enterprise security platforms. Across Microsoft and earlier roles, he brings 25+ years of enterprise engineering experience.

Today he brings that institutional rigor to organizations that need AI to work securely at scale — without the overhead of a large consultancy.

Microsoft Defender for Endpoint Defender for Apps O365 IAM Zero Trust LLM / RAG MLOps Azure Agentic systems MCP

Experience

Lead Architect & Builder
Applied AI Portfolio · 2025 – Present
Architected, built, and launched a portfolio of production-grade AI applications, demonstrating end-to-end capability with modern LLM infrastructure:
  • – StackAlpha: AI-powered investment research platform processing earnings calls and podcasts via complex RAG pipelines.
  • – CephNinja: AI cephalometric analysis SaaS for orthodontists. Multi-language, globally deployed with integrated billing.
  • – SMB AI Assistant: Developing a RAG-based AI assistant designed to streamline operations and handle 24/7 customer interactions.
Principal Engineering Manager
Microsoft Corporation · Jan 2002 – Jul 2025
Led Web Defense Services at Defender for Endpoint. Built and scaled App Governance at M365 Security. Led IAM, RBAC and Secure Orchestration at O365.

Approach

A structured path from problem to solution

Engagements are scoped to deliver value quickly. Most start with a focused discovery and move into a fixed-scope assessment or a time-boxed execution sprint.

01

Discovery call

A focused 45-minute session to understand your architecture, team, and the specific challenge you are trying to solve.

02

Fixed-scope assessment

A structured review of your AI stack, security posture, or delivery bottlenecks — delivered as a prioritized written recommendation set.

03

Engagement design

Based on findings, we agree on a time-boxed engagement: advisory retainer, embedded sprint, or a tightly defined implementation package.

04

Execution and handoff

Hands-on delivery with your team — with clear documentation, knowledge transfer, and defined success criteria throughout.

Industries served

Built for regulated, high-stakes environments

Best fit for teams where reliability, security, and operational rigor matter more than hype.

Enterprise SaaS
AI feature integration, security posture, MLOps maturity
Financial services
Compliance-first AI, signal extraction, data governance
Cybersecurity
Threat intelligence automation, IAM, zero trust architecture
Cloud infrastructure
Multi-cloud AI pipelines, cost architecture, observability
Venture-backed scaleups
Technical due diligence, scaling engineering orgs, CTO advisory

Ready to secure your AI roadmap?

Discuss your current infrastructure and identify where deep expertise in cloud security and high-scale AI platforms can move the needle.

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Contact

Let's discuss your architecture

Most engagements begin with a no-obligation discovery call. All inquiries are kept strictly confidential.

Typical response time Within 24 hours
Engagement types Advisory retainer, fixed-scope assessment, embedded sprint
Typical budget Assessments typically start at $7.5k; retained work is scoped separately
Based in Seattle / Bothell, WA — available globally
Confidentiality NDA available upon request

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