Pierre Kpodar
St. Louis,MO
Summary
Dynamic AWS Solutions Architect and Senior Infrastructure Specialist with over 10 years of experience designing, scaling, and securing cloud-native, enterprise-grade architectures. Proven expertise in building AWS Bedrock–powered AI platforms, RAG pipelines, and event-driven systems that enable intelligent document processing, semantic search, and decision support at scale
Overview
11
11
years of professional experience
1
1
Certification
Work History
Lead Machine Learning Engineer / Cloud Engineer
Centene
01.2021 - Current
- Engineered and deployed cloud-native, high-throughput document intelligence pipelines using AWS Bedrock and retrieval-augmented generation (RAG) architectures, enabling accurate information extraction, semantic search, and AI-powered summarization across large document corpora.
- Architected and maintained enterprise-grade CI/CD platforms (Jenkins, GitLab CI, GitHub Actions) to support continuous delivery of AI services, automated testing, and infrastructure automation with Terraform and CloudFormation.
- Led end-to-end deployment of production AI/ML workflows across distributed AWS environments, leveraging Bedrock foundation models, vector databases, and event-driven architectures, with observability via Prometheusand Grafana to optimize latency, throughput, and model performance.
- Designed and operated large-scale logging and observability pipelines using the ELK Stack (Elasticsearch, Logstash, Kibana) to monitor AI inference, RAG retrieval quality, and complex microservice interactions in distributed systems.
- Served as systems administrator for secure, multi-tenant AI infrastructure, configuring Linux-based environments, IAM policies, VPC networking, and data access controls to support compliant, scalable RAG and Bedrock-powered applications.
CEO / Technical Lead
Mawu, LLC
01.2015 - Current
- Led the architecture, design, and delivery of end-to-end client solutions across cloud infrastructure, full-stack applications, and AI/ML systems, ensuring scalability, reliability, and long-term maintainability.
- Built and maintained mission-critical middleware for the State of Missouri and the City of St. Louis, delivering highly reliable, persistently available systems that supported government operations with strict uptime and security requirements.
Senior Consultant
Slalom, LLC
01.2018 - 11.2025
- Optimized CI/CD pipelines for complex, multi-platform applications by introducing parallelized build and execution strategies, significantly improving release throughput across Windows, macOS, and containerized environments.
- Designed and built scalable ML deployment pipelines for Fortune 50 healthcare clients, including automated feature extraction, model packaging, and production rollouts.
- Containerized ML training and inference workloads and deployed them to Kubernetes (EKS) and AWS Fargate, demonstrating strong expertise in container orchestration and cloud-native ML infrastructure.
- Migrated statistical research code into modern microservices, enhancing performance, maintainability, and reliability while establishing automated build and testing workflows.
- Developed reusable Terraform modules supporting ML tooling, ELT pipelines, and automated cloud infrastructure provisioning across multiple environments.
- Collaborated with data science teams to bring models from experimentation to production, improving reliability, observability, and operational efficiency of ML systems.
Technical Lead / Full Stack Engineer
Aerial Insight, LLC
01.2015 - 01.2017
- Designed and built a full AWS-based platform for drone imagery and LiDAR ingestion, data annotation workflows, and automated CNN training pipelines (PyTorch, Keras, YOLO) for crack detection on utility insulators.
- Developed and deployed custom computer vision models to run directly on drone payload hardware, enabling real-time defect detection and reducing manual inspection time for utility field teams.
- Implemented GPU-accelerated training workflows for large-scale image processing, gaining practical experience with high-throughput compute, model optimization, and data handling similar to HPC and cluster-based environments.
- Created automated data pipelines for preprocessing, labeling, training, validation, and deployment, improving iteration speed and model accuracy across multiple inspection scenarios.
Education
Columbia College - Computer Science
Columbia College
Columbia05-2011
Skills
- AWS cloud architecture design
- Generative AI integration
- Retrieval-augmented generation expertise
- Semantic search proficiency
- MLOps implementation skills
- Infrastructure automation expertise
- Cloud observability and monitoring
- Docker and Kubernetes experience
- Linux system administration
- Event-driven architecture design
- Experience with AWS, GCP, and Azure
Certification
AWS Solutions Architect
Timeline
Lead Machine Learning Engineer / Cloud Engineer
Centene
01.2021 - Current
Senior Consultant
Slalom, LLC
01.2018 - 11.2025
CEO / Technical Lead
Mawu, LLC
01.2015 - Current
Technical Lead / Full Stack Engineer
Aerial Insight, LLC
01.2015 - 01.2017
Columbia College - Computer Science
Columbia College