benefield

Brett Benefield

AI Engineer · Multi-agent systems · Austin, TX

I design multi-agent systems and get them from proof of concept into production.

14 years of software engineering, 4 in applied data science and AI. Most recently I led a LangGraph-based agent platform at IBM from first prototype to live deployment.

Get in touch Résumé (PDF) LinkedIn
An orchestrator routes each request to triage, enrichment and summary agents, which share a layer of MCP tools. Incoming request OrchestratorLangGraph · shared state Triageagent Enrichmentagent Summaryagent MCP servers and toolsAPIs · vector search · data sources · observability
The general shape of the agent platform I led at IBM.
14+years in software engineering
3×faster triage after my agent platform shipped
PoC → prodled the platform end to end
12patents from earlier hardware work

Selected work

2015 – now
IBM · AI Engineer · 2022 – present

Multi-agent platform, from prototype to production

I led the architecture and delivery of a multi-agent platform that triages, enriches and summarizes security alerts. I owned it from the first proof of concept through live deployment.

  • Designed the LangGraph orchestration, including how agents share state, recover from errors and report what they're doing. The team has since adopted these patterns.
  • Built structured prompt chains and context architectures that keep agent output consistent when inputs vary a lot.
  • Led technology choices across the AI stack, weighing latency, cost and maintainability.

Result: analysts triage 3× faster.

LangGraphMCPAnthropic · OpenAI · GeminiFastAPIKafka
IBM · AI Engineer · ongoing

Mentoring engineers on agentic AI

I coach junior engineers on agent design patterns, LangGraph orchestration and how to evaluate LLM output. I also set code review and testing standards for the agent pipeline.

LLM evaluationCode review
IBM · Automated Systems Architect · 2021 – 2022

ML fault routing and test orchestration

I trained a Random Forest model to map noisy firmware error codes to hardware faults. It created tickets automatically, filled in the diagnostic details and sent them to the right team. I also led a team across the US, India and China that built test orchestration for z/OS, Linux and proprietary OS environments.

Result: validation overhead down 12%.

scikit-learnTest automation
SMU · M.S. Data Science thesis · 2019

Transformers for compliance classification

For my thesis I applied NLP and transformer models to sort regulatory compliance requirements for enterprise products into categories.

NLPTransformers
IBM · EMC Engineer · 2015 – 2021

Automated analysis of radiated emissions data

I replaced manual log review with automated pipelines that found patterns in emissions test data. I also built a remote lab system in Python so tests could run overnight without anyone on site. Statistical analysis traced one emissions problem to a fiber optic connector, which avoided an expensive switch redesign.

PythonStatistics

Path

Hardware → data → agents
  1. 2010

    B.S. Electrical Engineering, Oklahoma State University

    Trained to think in signals, systems and failure modes.

  2. 2015

    Electromagnetic Compatibility Engineer, IBM

    Automated data collection and analysis on mainframe hardware. Earned 12 patents.

  3. 2019

    M.S. Data Science, Southern Methodist University

    Thesis on NLP and transformer models.

  4. 2021

    Automated Systems Architect, IBM

    Led a team across three countries. Shipped ML-based fault routing.

  5. 2022

    AI Engineer, IBM

    Architect of a production multi-agent platform.

Toolkit

Agents & LLMs

Multi-agent orchestration, LangGraph, LangChain, MCP servers, context and prompt engineering, Anthropic, OpenAI, Gemini, Watson

Languages

Python, Java, C++, SQL, Bash

Backend & APIs

FastAPI, Flask, Pydantic, SQLAlchemy, PostgreSQL, Kafka, REST

Data

Vector databases, PySpark, Pandas, Elasticsearch, NiFi, ETL pipelines, data modeling

Infrastructure

Kubernetes, CI/CD, Git and GitHub, automated testing frameworks, IBM Cloud

Practice

Architecture design, code review, technical mentorship, dependency management

About

I started as an electrical engineer, chasing electromagnetic interference on IBM mainframes. That work taught me to look for the root cause and to automate anything I had to do twice. Over time it led me to data science and then to LLM-based agents.

Now I focus on the hard part of agentic AI: getting agents to coordinate reliably, recover when something fails, and show what they're doing well enough that a team can trust them in production. I'm looking for an AI Engineer role where I can build multi-agent systems.

Let's talk

Open to AI Engineer roles focused on multi-agent systems. Based in Austin, TX.

linkedin.com/in/brett-benefield