Shridhar Pathak
AI & ML · Strategy · Enterprise systems

Making AI useful to teams, accountable to leaders, and scalable for the enterprise.

I lead AI & ML at Moderna, connecting research-grade models to production outcomes. Previously shipped multi-agent voice AI at Amazon Alexa at $100M-program scale. MBA at MIT Sloan (cross-registered at Harvard Business School), and Founder & Advisor on a stealth enterprise agent evaluation platform—tracing, observability, and evals before agents hit production.

Boston, MA (Brookline) · +1 214 794 6073 · shripathmit@gmail.com

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Professional summary

Fifteen years in distributed systems and multi-agent AI—scaling orgs past 50 people and $100M-class programs—linking LLM research to production revenue.

MIT Sloan MBA (HBS cross-registration) while building a stealth enterprise agent-eval venture as Founder & Advisor.

Expand for full narrative

AI engineering leader with 15 years in distributed systems and multi-agent AI. Strong history scaling global organizations from inception to 50+ people and managing programs exceeding $100M scale (Amazon Alexa). MBA candidate at MIT Sloan (2026), cross-registered at Harvard Business School, specializing in AI transformation and platform economics—connecting advanced LLM research to high-scale production revenue. Senior Director, AI & ML at Moderna; former Amazon Alexa and Amazon Retail. Founder & Advisor of a stealth enterprise agent evaluation platform.

Unique combination of deep technical engineering and executive strategy: major launches at Amazon (Alexa, international voice shopping, India retail integration, Southeast Asia retail velocity) and GenAI transformation at Moderna. Experience spans retail, voice AI, regulated enterprise AI, and stealth venture building.

Current focus

Venture · Impact · Advisory

Venture

Stealth agent evaluation

Tracing, observability, and human + automated evaluation for enterprise AI agents before production.

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Impact

Moderna & Alexa

GenAI roadmaps, multi-agent voice AI at global scale, international retail velocity, and regulated deployments.

View outcomes

Advisory

Education & counsel

MIT Sloan EMBA (HBS cross-reg), Stanford Seed, Health Galaxy founding tech advisor, and structured profile for agents.

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Current

Stealth venture

Founder & Advisor · Enterprise agent evaluation · 2025 – Present

Stealth — product story & milestones

Enterprise agent evaluation platform: tracing and observability for AI agents (actions, decisions, outputs), plus automated and human evaluation to catch regressions before launch and improve quality over time.

50+ enterprise discovery calls; three design-partner pilots; validated seed-stage pricing within six months. MVP in progress.

Expand for innovation, value prop & achievements

Key innovation

Agent evaluation & performance intelligence

  • End-to-end tracing of every AI agent action, decision, and output
  • Automated and human-in-the-loop scoring to continuously improve agent quality
  • Catch regressions before production; compare agent versions side-by-side

Value proposition

  • Manage AI agents the way you manage employees—with performance reviews, accountability, and continuous improvement
  • Replace black-box AI deployments with full operational transparency
  • Scale digital workers confidently without quality or compliance risk

Achievements

  • 50+ enterprise discovery and validation conversations
  • Three design-partner pilots underway
  • Validated seed-stage pricing model within six months
  • Technical architecture, MVP, and GTM strategy

Impact

Selected outcomes

Impact overview

Industry-first multi-agent AI on Alexa, celebrity and Hey Disney experiences, and international voice shopping—including +500 bps engagement in the first month of a major celebrity launch and a $50M+ ARR-class platform narrative.

Led Southeast Asia retail launch (Project Nautilus) and voice AI for Amazon India at millions of users; at Moderna, GenAI roadmap for 20+ apps, 35+ org, OpenAI/AWS partnerships, and expected timeline compression in R&D and clinical ops.

Expand for full outcome lists
  • Shipped industry-first multi-agent conversational AI on Alexa; celebrity and character experiences (CNN, CNET, About Amazon).
  • +500 bps engagement in the first month of a major celebrity voice launch.
  • Led Amazon’s first retail launch in Southeast Asia (Project Nautilus, Singapore) and expanded Alexa Voice Shopping to ten international markets (US, India, Japan, Canada, France, Italy, Spain, Mexico, Ireland, Australia).
  • Architected voice AI for the Amazon India retail app at millions of daily users; built teams from 0 to 16+.
  • At Moderna: GenAI roadmap for 20+ enterprise applications; 35+ person engineering org from the ground up; multi-million-dollar OpenAI and AWS partnerships; expected ~30% reduction in R&D and clinical operation timelines; governance fit for regulated biopharma.

Product launches & innovation

  • Pioneered multi-agent AI framework on Alexa enabling personality switching (industry first)
  • Launched celebrity voice experiences: Melissa McCarthy, Shaq, Amitabh Bachchan
  • Delivered Hey Disney voice assistant (CNN, CNET, major media)
  • Led Amazon’s first retail launch in Southeast Asia (Project Nautilus — Singapore)
  • Expanded Alexa Voice Shopping to ten countries (US, India, Japan, Canada, France, Italy, Spain, Mexico, Ireland, Australia)
  • Architected voice AI integration for Amazon India retail app (millions of daily users)

Technical leadership

  • Built teams from 0 to 16+ across multiple product initiatives
  • Architected systems processing millions of daily requests with low latency
  • Designed scalable infrastructure for high-volume ML-driven voice interactions
  • Created measurement and analytics frameworks treating metrics as engineering challenges
  • Integrated LLMs into Moderna enterprise applications across R&D, manufacturing-adjacent workflows, and quality—with governance fit for regulated biopharma

Business impact

  • +500 basis point engagement increase in first month of celebrity voice launch
  • Enabled revenue expansion through international Alexa market launches
  • Positioned Moderna as an AI leader in enterprise biopharma applications and partnerships
  • Built measurement infrastructure tying technology to business outcomes
  • Created frameworks for AI governance in highly regulated industries

Proof

Signature stories

Short case-style snapshots—problem, role, and measurable outcome.

Voice AI at scale (Amazon Alexa)

Problem → multi-agent voice experiences & international growth

Problem: Ship reliable, engaging celebrity and multi-agent voice experiences while expanding Alexa into new markets.

Role: Tech lead and senior TPM for multi-agent AI initiatives; led international Alexa launches and measurement frameworks.

Outcome: +500 bps engagement lift in the first month of a major celebrity voice launch; enabled revenue expansion through international market launches and analytics that tied product work to business results.

GenAI at enterprise scale (Moderna)

Problem → roadmap, org, and partnerships

Problem: Stand up GenAI across R&D, clinical, and operations with measurable ROI, secure cloud paths, and executive alignment—not slide decks.

Role: Senior Director, AI & ML; built a 35+ person engineering organization; C-suite translation; OpenAI and AWS strategic partnerships.

Outcome: Roadmap for 20+ enterprise applications; expected material compression of R&D and clinical operation timelines; production LLM workflows on AWS with governance for regulated environments.

Enterprise AI agents (stealth)

Problem → observability and evaluation

Problem: Enterprises need to treat AI agents as accountable digital workers—with visibility, evaluation, and continuous improvement before wide release.

Role: Founder & Advisor; product vision, MVP, and enterprise discovery for an agent evaluation platform.

Outcome: 50+ enterprise discovery calls; three design-partner pilots; validated seed-stage pricing within six months; MVP with tracing, scoring, and regression detection.

Organizations & visibility

Moderna · Amazon · MIT Sloan · Harvard Business School (cross-reg.)

Press: CNN Business, CNET, About Amazon (see More for detail)

Background

Experience

Each role shows a short overview; expand for responsibilities and impact. TIFR and campus roles are under More.

Senior Director, AI & ML — Moderna Cambridge, MA · July 2023 – Present

GenAI roadmap for 20+ enterprise applications; built a 35+ person engineering organization from the ground up; production LLM workflows on AWS for global manufacturing.

C-suite translation of AI capabilities; multi-million-dollar strategic partnerships with OpenAI and AWS; expected material compression of R&D and clinical operation timelines.

Expand for responsibilities & impact

Key responsibilities

  • Define and execute enterprise GenAI strategy across R&D, clinical, and operations—including partnership strategy with OpenAI and AWS
  • Architect scalable AI solutions on AWS and open-source frameworks; security, scalability, and regulatory compliance
  • Partner with product, engineering, and external stakeholders on AI-driven process optimization and ROI
  • Integrate multimodal AI (text, image, structured data) into high-stakes workflows with governance fit for regulated biopharma

Impact

  • Roadmap spanning 20+ enterprise applications with expected ~30% reduction in R&D and clinical operation timelines (portfolio-level target)
  • Engineering organization of 35+ members built from inception for production-grade LLM delivery
  • Secured multi-million-dollar investments and partnerships; shaped measurable business outcomes with executive stakeholders
Sr. Manager & Tech Lead — Amazon Alexa Conversational AI & multi-agent systems · June 2018 – July 2023

Large-scale conversational AI and multi-agent orchestration for Alexa worldwide—40 direct reports and 145 partner-team reports across 8+ countries.

First multi-agent switching framework (celebrity and Disney agents); $50M+ ARR-class business model; Voice Shopping in ten countries; India retail app at millions of DAU. CNN, CNET, About Amazon.

Expand for achievements & media

Key achievements

  • Architected and launched Alexa’s first multi-agent conversational switching framework—Melissa McCarthy, Shaquille O’Neal, Amitabh Bachchan, Disney (Hey Disney)
  • Core infrastructure for a business model generating over $50M in annual recurring revenue (celebrity and partner agents)
  • Rolled out Alexa Voice Shopping in the US, India, Japan, Canada, France, Italy, Spain, Mexico, Ireland, and Australia
  • Led integration of speech recognition, NLP, contextual understanding, and response orchestration; APIs and ML endpoints for the Amazon India retail app at millions of daily active users
  • Built and scaled multi-disciplinary teams; cross-organizational alignment across Alexa AI, retail, device, and international engineering
  • +500 bps engagement in the first month of a major celebrity launch

Media: CNN, CNET, About Amazon

Manager & Tech Lead — Amazon Retail International expansion · June 2015 – Dec 2018

Cut Amazon’s standard three-year country launch timeline to nine months for first retail entry in Southeast Asia—sole technical owner aligning 26 teams and seven global organizations.

Region’s first end-to-end digital marketing and last-mile logistics stack; two-hour delivery in Singapore; proprietary systems fulfilled 100% of regional orders.

Expand for Project Nautilus detail

Project Nautilus — Singapore

  • Decoupled legacy US-centric systems to create a lightweight, region-specific operating model for flagship launch goals
  • Architected marketing technology stack from the ground up
  • Integrated ad targeting, email triggers, and inventory–marketing coordination
  • Built measurement infrastructure—metrics as an engineering discipline
  • Launched Alexa Voice Shopping in India, Japan, Canada, France, Italy, Spain, Mexico, Ireland, and Australia (during overlapping international expansion scope)
Software Development Engineer — Amazon.com Amazon Register (POS) · June 2012 – June 2015

High-scale distributed services and fraud detection for Amazon Register—global merchant onboarding, financial portal integrations, fault-tolerant payment flows in Java and C++.

Expand for additional context

Tech lead across Seattle and Bangalore: cross-site delivery velocity, customer-facing widgets and service endpoints, and technical onboarding for thousands of new merchant partners.

Education & advisory

Education

Consulting & advisory

Founding Tech Advisor — Health Galaxy AI Heart Score app · 2024 – Present

Founding tech advisor to the CEO on scaling operations and AI-enabled business models—including AI-ready architecture for the AI Heart Score app.

Expand for scope

Scope

  • AI-ready architecture and technical direction for product scale
  • Operating model and AI-enabled go-to-market alignment with leadership
Stanford Seed Consultant Global founders · June 2025 onward

Strategic advisor to global founders on scaling operations and AI-enabled business models—especially in developing economies.

Digital transformation, process efficiency, and applied lessons from large-scale tech leadership.

Expand for contributions

Contributions

  • Technology adoption and digital transformation guidance
  • Process optimization and operational efficiency
  • Mentorship on scaling in resource-constrained contexts
  • Applied lessons from global tech to emerging markets

Expertise

Technical & strategy

Skills & domains

AI/ML: LLMs, LLM orchestration, agentic and multi-agent systems, NLP, speech, multimodal AI, MLOps, governance. Cloud: AWS, distributed systems, APIs, data pipelines, security and compliance.

Engineering: Python, Java, JavaScript, C/C++, SQL, major databases. Business: product, GTM, modeling, executive communication, org transformation.

Expand for full categorized lists

Artificial intelligence & ML

  • LLMs — GPT, Claude, Llama-class architectures
  • LLM orchestration & fine-tuning strategy
  • Agentic frameworks & multi-agent systems
  • NLP; speech recognition & synthesis
  • Predictive analytics & ML pipelines
  • Multimodal AI (text, image, structured data)
  • MLOps
  • AI governance & responsible AI frameworks

Cloud & infrastructure

  • AWS — compute, storage, ML services
  • Distributed systems; APIs & microservices
  • Big data pipelines & data engineering
  • Scalability, performance, security & compliance

Programming & development

  • Languages: Python, Java, JavaScript, C, C++, SQL
  • Databases: MySQL, DynamoDB, PostgreSQL
  • REST, GraphQL, WebSockets
  • Git, CI/CD, Agile
  • Data structures, algorithms, system design

Business & strategy

  • Product strategy & roadmaps
  • GTM & business model design
  • Financial modeling & TAM/SAM/SOM
  • Stakeholder & executive communication
  • Cross-functional leadership & change management

Additional

Certifications, leadership, philosophy

Short previews below; expand any block for the full write-up.

Certifications & awards

Rice University leadership certificates (2018), Coursera AI coursework, IIT Bombay ML/AI lab fellowships, and KVPY national science fellowship (2005–09).

Expand for full list

Leadership development (Rice, 2018)

  • Leadership Development for Engineers
  • Personal Leadership Development; Leading High Performing Teams
  • Relationship Management
  • Self-Awareness and the Effective Leader

Technical

  • AI for Everyone — Coursera
  • Machine Learning Specialization — in progress

Fellowships

  • IIT Bombay — three fellowships in Machine Learning and AI research laboratories

Academic honors

  • KVPY Fellowship (2005–09) — Young Scientist, Engineering Stream; only engineering student selected in 2005 EB stream in India
Leadership & community

Research at TIFR on GRAPES-3 / CERN; orientation leadership for ~1,700 UTD freshmen; NSBE graduate chair; IEEE communications lead at PICT.

Expand for role-by-role detail

Junior Research Fellow — TIFR (July 2009 – April 2010), Mumbai

  • Algorithms for monitoring scintillator detectors; GRAPES-3 / CERN
  • ROOT framework and C++

UTD Orientation Team Mentor (2011)

  • Led orientation for ~1,700 freshmen
  • Group leader for 100 students; cohorts up to 25

NSBE — UTD Graduate Chair

  • Industry–graduate bridge; recruiting and workshops

IEEE PRO — PICT (2006–08)

  • Communications and events for ~700-member chapter
Publications & media

Press: CNN Business, CNET (Hey Disney), About Amazon India (Amitabh Bachchan). Technical: GRAPES-3 work, internal AI governance talks, voice AI architecture docs.

Expand for full breakdown

Media

  • CNN Business — Alexa celebrity personalities
  • CNET — Hey Disney at Disney World
  • About Amazon (India) — Amitabh Bachchan partnership
  • Additional coverage of Alexa innovation and expansion

Technical

  • GRAPES-3 (CERN) — scintillator monitoring algorithms
  • Internal talks on AI governance and multi-agent systems
  • Architecture documentation for scalable voice AI
Professional philosophy

I build at the intersection of engineering depth and business strategy—systems that ship, scale, and tie cleanly to outcomes.

Measurement is an engineering problem; on the stealth agent-eval venture, focused on trustworthy, auditable multi-agent enterprise AI.

Expand for full essay

I operate at the intersection of deep technical engineering and high-level business strategy. My career has been defined by building systems that don’t just work technically, but solve real business problems and create measurable value.

From Amazon’s first retail launch in Southeast Asia to AI transformation at Moderna, successful technology leadership requires: (1) Technical depth—architect solutions that scale; (2) Business acumen—tie decisions to outcomes; (3) Customer focus—build for real users and measurable impact.

I treat measurement as an engineering challenge—not a dashboard exercise—that determines whether a business succeeds or fails. On the stealth enterprise agent evaluation platform, the focus is multi-agent enterprise AI that is trustworthy, auditable, and compliant—the unlock for automation at scale.

What I bring to organizations

Bilingual technical and executive communication; 15+ years across Fortune 500 and startups; global launches in ten countries (Voice Shopping footprint).

Founder & Advisor on a stealth agent-eval venture—comfort with ambiguity, iteration, and outcome-led execution.

Expand for four dimensions

Bilingual communication

  • Fluent in technical and business languages
  • Architect with engineers; present strategy to the C-suite
  • Bridge technical teams and business stakeholders

Proven track record

  • 15+ years on complex, high-impact technical initiatives
  • Retail, voice AI, healthcare, enterprise software
  • 0-to-1 launches and market expansions
  • Fortune 500 and startup environments

Global perspective

  • International expansion across 10 countries (Alexa Voice Shopping footprint)
  • US, India, Singapore, Vietnam, and global markets
  • Cross-cultural teams and multi-jurisdiction awareness

Entrepreneurial mindset

  • Building a stealth enterprise agent evaluation platform from the ground up
  • Comfort with ambiguity and rapid iteration
  • Outcomes over outputs; strategy, resources, execution
Closing note

A career focused on technology that matters—products that ship and create real business value.

Expand for full closing

This portfolio reflects a career dedicated to building technology that matters—systems that scale, products that ship, and solutions that create real business value. Whether leading at global tech companies or building startups from scratch, I stay focused on one question: How can we use technology to solve problems that actually matter?

Machine-Readable Interface

Data Endpoints

/profile.json application/json

Versioned structured profile — work history, skills taxonomy, education, current venture (stealth), fellowships, consulting, selected impact, and an agentHints block. Fields: version, lastUpdated.

Open
/llms.txt text/plain

Navigation index following the llms.txt convention. Site structure, content policy, and consumption instructions for AI agents.

Open
/resume.pdf application/pdf

Downloadable resume / CV.

Download
JSON-LD embedded in <head>

Person + WebSite schema.org markup for search engines and knowledge graphs.

Page Content Map

The human view uses <details> collapse/expand toggles. Basic scraping captures only preview text — use /profile.json for complete structured data.

SectionAnchorHidden behind <details>
Editorial landing#main (top)Hero, projects, insights, experience snapshot, contact; then full sections below
Stealth venture#ventureInnovation, value prop, achievements
Selected outcomes#highlightsFull impact lists by category
Signature stories#storiesNone — always visible
Experience (4 roles)#experienceEach role's responsibilities & impact
Education (3 degrees)#educationMIT coursework list
Skills & domains#expertiseFull categorized skill lists
Certs, leadership, philosophy#moreAll sub-sections expanded content

Structured Profile

Parsed from profile.json — navigate by section instead of reading raw JSON.

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Raw JSON

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