12+ Years in Technology

Carlo
Perottino

Technology Leader & Builder

Building intelligent systems and leading high-performing teams across AI, cloud infrastructure, and enterprise transformation.

Explore My Journey

Experience

Charlotte, NC · Healthcare & Life Sciences

$33.4M in wins across 36 opportunities

Highlights

  • › Design enterprise AI/ML architectures spanning computer vision, agentic AI, and generative AI for healthcare and life sciences organizations
  • › Build and prototype multi-agent systems, RAG platforms, and serverless SaaS applications, delivering functional MVPs within days
  • › Lead technical workshops, hackathons, and executive briefings across the US and EMEA
  • › Architect compliance-aware AI solutions for regulated environments including HIPAA, GxP, and GDPR
  • › Directly led wins totaling $33.4M across 36 closed opportunities in first year
  • › Led largest-ever Clash of Agents competition at healthcare innovation summit: 51 participants, perfect 5.0 CSAT
  • › Executed 2-day hackathon in Prague training analysts to build full GenAI applications with 100% satisfaction

Key Projects

Enterprise Video Analysis Platform

Technical solution architecture for laboratory video analysis across thousands of cameras with custom ML models designed for HIPAA and GDPR compliance.

3,300+ cameras

Agentic AI Strategic Partnership

Expert consultation on agentic AI capabilities positioning for multi-year strategic investment agreement.

$30M+ engagement

Scientific Workflow SaaS

Serverless multi-agent SaaS for research workflow automation covering literature search, protocol creation, and lab management with multi-tenant architecture.

MVP in 3 days

M&A Compliance Platform

Agentic RAG system with async pipelines for automated regulatory compliance assessment.

MVP in 3 days

GenAI Productivity Transformation

Enabled GenAI use case that improved productivity by 99%, reducing an 80-hour manual process to 25 minutes.

80 hrs → 25 min

Technologies

Amazon BedrockSageMakerLangGraphStrands SDKLambdaStep FunctionsECSCDKAgentCore

Charlotte, NC

6 AI agents orchestrated in production

Highlights

  • › Built full-stack multi-agent competitive intelligence platform from zero to production
  • › Orchestrates 6 specialized AI agents with supervisor-pattern topology and concurrent tool execution
  • › Engineered RAG pipeline with vector search using LangChain and PGVector (3,072-dim embeddings)
  • › Designed multi-model slide generation pipeline: LLM designs layouts from 8 visual archetypes, image model renders visuals, PDF engine assembles output
  • › Shipped FastAPI backend with 20+ endpoints, async job orchestration, and Cognito JWT auth
  • › Built React 19 + TypeScript dashboard with structured insight cards and real-time job status polling
  • › Provisioned complete AWS environment via Terraform (10 modules) with ECS Fargate and RDS PostgreSQL

Key Projects

Multi-Agent Intelligence Engine

Supervisor-pattern topology orchestrating research, persona profiling, market analysis, strategic positioning, content generation, and meeting prep agents.

6 agents · Concurrent

RAG Pipeline & Vector Search

Document ingestion and retrieval pipeline with metadata-enriched chunking and company-scoped similarity search.

3,072-dim embeddings

AI-Powered Slide Generation

Three-stage pipeline: LLM designs structured layouts, image model renders each slide, PDF engine assembles the final output.

8 visual archetypes

Full-Stack Production Platform

FastAPI + React 19 dashboard with admin console, feedback system, and Terraform-managed AWS infrastructure.

20+ endpoints · 10 TF modules

Technologies

PythonStrands SDKFastAPIReact 19LangChainPGVectorTerraformOpenAIGoogle Gemini

Charlotte, NC · AI & Data Practice

1K+ users · 70+ countries · ~$28B forecasted

Highlights

  • › Led delivery of next-generation commercial forecasting platform forecasting ~$28B in revenue, serving 1,000+ users in 70+ countries
  • › Oversaw technical delivery for ~$25M program over 2.5 years, managing 30+ developers across 5 countries
  • › Managed $12M engagement portfolio with full P&L ownership as Senior Manager
  • › Grew team from initial founding to 50+ members through rigorous talent acquisition and capability expansion
  • › Architected event-driven simulations framework enabling large-scale financial modeling for a $2B franchise
  • › Led MLOps workflow implementation for time-series forecasting enrichment using Prophet
  • › Designed graph-based recommendation engines and knowledge graph platforms across energy and travel industries
  • › Built NLP pipelines for intelligent document processing and automated tax credit identification
  • › Implemented real-time data streaming and event-driven architectures for enterprise analytics
  • › Drove DevOps transformation with zero-touch deployments in GxP-regulated environments
  • › Developed and closed new business worth $10M+ across capability expansions
  • › Mentored 3+ team members to promotions and expanded leadership roles

Key Projects

Commercial Forecasting Platform
★

Led delivery of enterprise forecasting platform covering ~$28B in forecasted revenue. Oversaw 30+ developers across 5 countries over 2.5 years. Architected on EKS with FastAPI, Cognito auth, and OPA-based authorization.

~$28B forecasted · 1K+ users · 70+ countries

Platform Expansion & Hardening

Managed $12M portfolio including event-driven simulations via AWS Batch, MLOps with Prophet, Kafka event bus, and a new platform support squad worth $1M/yr.

$12M portfolio · $2B franchise

Graph-Based Recommendation Engine

Graph-based product recommendation system for a major travel & entertainment company using Neo4j algorithms and Kafka-based data streaming from distributed sources.

Neo4j + Kafka

Knowledge Graph Platform

Knowledge Graph POC aggregating project planning and cost data for a multinational energy company. NLP techniques for automated tax credit identification.

BI time: 5 days → 4 hours

Supply Chain Analytics Platform

Spark-based data ingestion framework enabling cloud migration. Built reusable interface for supply chain forecasting model industrialization.

Cloud migration · Spark

Clinical Data Hub & DevOps

DevOps revamp in GxP-regulated data platform. Zero-touch GitOps deployments, hub-and-spoke data architecture, and release cycle optimization.

GxP compliant · 4-5 wk releases

Technologies

PythonFastAPIKubernetesEKSTerraformKafkaNeo4jSparkSageMakerPostgreSQLJenkinsDockerAWS BatchOPA

Cincinnati, OH

~1,600 engineering hours reclaimed per month

Highlights

  • › Built AWS-based data collection platform monitoring 15,000+ compute assets across the enterprise
  • › Discovered 150+ critical misconfigurations on 50+ applications through programmatic analysis
  • › Developed ML models for change risk assessment, reducing time-to-resolution by up to 50%
  • › Architected Kafka-driven self-healing automation framework, reclaiming ~1,600 engineering hours per month
  • › Modeled enterprise connectivity networks using Neo4j graph analytics for dependency-aware incident response
  • › Reclassified ~15% of compute assets to proper criticality, vastly improving support posture
  • › Led product strategy for infrastructure intelligence tooling serving enterprise aviation operations
  • › Pitched and secured leadership investment for new automation platform

Key Projects

Infrastructure Intelligence Platform

Data collection and analytics platform monitoring enterprise compute assets. Programmatic configuration analysis and remediation tracking.

15K+ assets · 150+ misconfigs

Self-Healing Automation Engine

Kafka-driven intelligent automation framework enabling user-driven, self-healing infrastructure operations with measurable reductions in manual intervention.

~1,600 hrs/mo reclaimed

Enterprise Graph Analytics

Neo4j-based connectivity modeling of enterprise infrastructure. Graph algorithms for centrality analysis and dependency mapping.

15% assets reclassified

Change Risk Assessment

ML models predicting high-risk infrastructure changes. Integration with change management workflow for proactive risk identification.

50% faster TTR

Technologies

PythonAWSKafkaSageMakerNeo4jPostgreSQLTerraformDockerElasticsearchFlaskJenkins

Greenville, SC

Highlights

  • › Managed 19-node Hadoop cluster for distributed computing and performance benchmarking
  • › Developed CNN-based image recognition systems for manufacturing quality analysis
  • › Benchmarked ML training algorithms across Spark MLlib and R frameworks
  • › Presented technical findings and benchmarking results to senior leadership

Key Projects

Hadoop Cluster & Benchmarking

Large-scale distributed computing environment management with performance benchmarking across Spark, Hive, and MapReduce.

19-node cluster

CNN Image Recognition

Neural network-based image recognition for manufacturing quality analysis using custom image processing and feature extraction.

Manufacturing analysis

Technologies

HadoopSparkPythonRCNNEMRHiveYARN

Cincinnati, OH

Highlights

  • › Bachelor of Science, College of Engineering & Applied Science
  • › President, CEAS Student Government: managed 26 officers, $140K budget, and 1,160 students
  • › President, IEEE Student Chapter: managed 8 officers and 130 students
  • › Supervised 13 committees focused on student experience, academic affairs, and career development
  • › AWS Certified Solutions Architect - Associate
  • › AWS Certified AI Practitioner
  • › AWS Certified Machine Learning Engineer - Associate

Earlier Experience

Diebold, Inc. Co-Op, Global Software Development North Canton, OH · 2013
Cincinnati Bell Technology Solutions Management Trainee Cincinnati, OH · 2012

Skills & Expertise

AI & Machine Learning

Agentic AIMulti-Agent SystemsRAGMLOpsLLMOpsNLPComputer VisionDistributed TrainingHITL Learning

Cloud & Infrastructure

AWS BedrockSageMakerLambdaECSStep FunctionsEMRTerraformDockerKubernetesServerless

Data & Analytics

SparkKafkaPostgreSQLNeo4jOpenSearchPGVectorEvent-Driven ArchitectureMicroservices

Languages & Frameworks

PythonSQLTypeScriptC#FastAPIReactLangGraphLangChainStrands SDK

About Me

Carlo Perottino

Based in Charlotte, North Carolina, originally from Ohio. Engaged to Madison, with two dogs, Arla and Chickpea. Outside of tech, I'm usually camping, backpacking, or hiking. I love skiing and am part of the Beech Mountain Ski Patrol.