Open to opportunities

CHARLES WARD

@charlesward

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Senior AI and backend engineer building scalable cloud systems and agent orchestration.

United States

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What I'm looking for

I seek roles building large-scale AI-backed systems and agent platforms with strong engineering practices, SLO-driven reliability, and cross-team impact.

I am a Senior AI and Backend Engineer with over 10 years of experience designing and shipping production-grade, cost-efficient cloud backends and multi-agent AI systems for global brands. I specialize in bridging applied AI research and engineering—architecting schema-validated reasoning workflows, hybrid Bedrock/OpenAI runtimes, and durable memory layers (Redis + pgvector) to enable reliable multi-agent collaboration and automation across commerce and supply-chain domains.

At Nike and prior at Pinterest and Amazon, I led platform work including RAG pipelines, embedding and inference scaling, observability, and SDKs for connector/agent publication, cutting latency and cost while improving model safety and rollout velocity. I bring hands-on expertise in Python, TypeScript, FastAPI, Kubernetes, and AWS, combined with a pragmatic focus on SLO-driven reliability, tooling, and cross-team enablement.

Experience

Work history, roles, and key accomplishments

Current

Senior AI & Agent Orchestration Engineer

Current

Nike, Inc

Jun 2021 - Present (4 years 7 months)

Architected schema-validated multi-agent reasoning workflows and a hybrid Bedrock/OpenAI runtime to optimize inference cost and contextual persistence, and led development of an Agent Marketplace SDK to automate insights from Salesforce, SAP, and Adobe Experience Cloud.

OpenAI API Redis Pgvector Python SDK Lang Chain

LLM Platform Engineer

Jun 2018 - May 2021 (2 years 11 months)

Productized RAG pipelines with safety filters and prompt-evaluation harnesses, and scaled embedding services on Kubernetes and AWS to reduce p95 latency ~30% while lowering infrastructure costs and standardizing embedding/feature registries.

RAG Kubernetes AWS Embeddings Prompt Evaluation AutoScaling Observability Python

Machine Learning Engineer

CortexForge Systems

Jan 2019 - Dec 2020 (1 year 11 months)

Deployed FastAPI inference on Fargate with CI/CD and blue/green deploys, built BERT-based semantic search and clustering to increase relevant-doc hit rates and reduce manual triage for support teams.

fastAPI AWS Fargate CI CD BERT Semantic Search Python Vector Databases

Junior AI Data Engineer

Amazon

Jan 2016 - Dec 2018 (2 years 11 months)

Built a LangGraph Bedrock/OpenAI multi-agent runtime with typed validators and guardrails, implemented a Redis + pgvector memory layer and telemetry to enable p95 latency and spend SLOs with Grafana alerts for on-call readiness.

LangGraph OpenAI API Redis Pgvector OpenTelemetry Grafana Python

AI Data Intern

Amazon

Sep 2014 - Dec 2015 (1 year 3 months)

Automated dataset ingestion and transforms using AWS Glue and Athena and produced evaluation notebooks in Python/Pandas to support internal model training.