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I am Anthony Abercrombie, an AI Agent Engineer with 8+ years building and deploying production AI systems. I currently develop and deploy agentic applications using LangChain, LlamaIndex, DSPy, and RAG architectures for enterprise customers including Uber, Tempus, and Lowe's. I have deep experience in Python and Go, cloud platforms (AWS, GCP, Azure), and system integrations via APIs and data pipelines. I excel at translating business needs into AI solutions and enjoy presenting technical demos to help customers realize value. I built and open-sourced an MCP server for natural language to GraphQL translation—demonstrating hands-on AI agent development and deployment. I also provide customer-facing guidance, gather requirements, and collaborate with product and engineering teams to design scalable architectures.…I am Anthony Abercrombie, an AI Agent Engineer with 8+ years building and deploying production AI systems. I currently develop and deploy agentic applications using LangChain, LlamaIndex, DSPy, and RAG architectures for enterprise customers including Uber, Tempus, and Lowe's. I have deep experience in Python and Go, cloud platforms (AWS, GCP, Azure), and system integrations via APIs and data pipelines. I excel at translating business needs into AI solutions and enjoy presenting technical demos to help customers realize value. I built and open-sourced an MCP server for natural language to GraphQL translation—demonstrating hands-on AI agent development and deployment. I also provide customer-facing guidance, gather requirements, and collaborate with product and engineering teams to design scalable architectures.

Anthony Abercrombie

AI Engineer, Data Scientist, Full Stack Developer, +1

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I am Anthony Abercrombie, an AI Agent Engineer with 8+ years building and deploying production AI systems. I currently develop and deploy agentic applications using LangChain, LlamaIndex, DSPy, and RAG architectures for enterprise customers including Uber, Tempus, and Lowe's. I have deep experience in Python and Go, cloud platforms (AWS, GCP, Azure), and system integrations via APIs and data pipelines. I excel at translating business needs into AI solutions and enjoy presenting technical demos to help customers realize value. I built and open-sourced an MCP server for natural language to GraphQL translation—demonstrating hands-on AI agent development and deployment. I also provide customer-facing guidance, gather requirements, and collaborate with product and engineering teams to design scalable architectures.…I am Anthony Abercrombie, an AI Agent Engineer with 8+ years building and deploying production AI systems. I currently develop and deploy agentic applications using LangChain, LlamaIndex, DSPy, and RAG architectures for enterprise customers including Uber, Tempus, and Lowe's. I have deep experience in Python and Go, cloud platforms (AWS, GCP, Azure), and system integrations via APIs and data pipelines. I excel at translating business needs into AI solutions and enjoy presenting technical demos to help customers realize value. I built and open-sourced an MCP server for natural language to GraphQL translation—demonstrating hands-on AI agent development and deployment. I also provide customer-facing guidance, gather requirements, and collaborate with product and engineering teams to design scalable architectures.

Available to hire

I am Anthony Abercrombie, an AI Agent Engineer with 8+ years building and deploying production AI systems. I currently develop and deploy agentic applications using LangChain, LlamaIndex, DSPy, and RAG architectures for enterprise customers including Uber, Tempus, and Lowe’s. I have deep experience in Python and Go, cloud platforms (AWS, GCP, Azure), and system integrations via APIs and data pipelines. I excel at translating business needs into AI solutions and enjoy presenting technical demos to help customers realize value.

I built and open-sourced an MCP server for natural language to GraphQL translation—demonstrating hands-on AI agent development and deployment. I also provide customer-facing guidance, gather requirements, and collaborate with product and engineering teams to design scalable architectures.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

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Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AI Solutions Engineer at Arize

February 1, 2025 - Present

Develop, configure, and deploy AI agents using LangChain, LlamaIndex, DSPy, and CrewAI frameworks; implement RAG pipelines and function calling for enterprise agentic applications. Conduct interactive demos and POCs; gather feedback and refine solutions to meet business objectives. Integrate AI agents with external systems via APIs, webhooks, and data pipelines; instrument OpenTelemetry tracing across Python, TypeScript, Go, Java, and .NET. Collaborate with product and engineering teams to translate customer requirements into AI agent solutions and become a trusted technical advisor for enterprise customers (Uber, Tempus, Lowe's) on architecture and scalability. Open-sourced MCP server for natural language to GraphQL translation with schema-based validation.

Senior Solutions Engineer at Transcend

June 1, 2023 - June 1, 2024

Gathered technical requirements from 50 enterprise customers and translated business needs into deployed solutions; achieved 84% retention rate and NPS of 38. Defined project milestones, created implementation plans, and coordinated execution with internal teams, reducing time-to-deployment by 67% (3 months → 1 month). Built system integrations connecting privacy infrastructure with customer CRMs, databases, and APIs; developed tooling in TypeScript, Go, and Python. Deployed containerized solutions on Kubernetes across AWS, GCP, Azure, and on-prem; implemented CI/CD pipelines and monitoring for production systems. Provided tight feedback loop to product and engineering teams—identified gaps, built custom tooling, and influenced roadmap through deployment learnings.

Senior Software Engineer, Data Platform at Bitly

April 1, 2022 - June 1, 2023

Led a 3-person team developing high-throughput Go microservices for real-time data processing at petabyte scale. Built system integrations connecting data pipelines with external APIs, databases, and analytics platforms using Apache Beam, Airflow, and BigQuery. Managed cloud infrastructure on GCP; implemented CI/CD pipelines, containerization, and monitoring using DataDog and Google Cloud Logging. Collaborated cross-functionally with product engineering and BI teams to gather requirements and deliver data-driven solutions.

Software Engineer – Usage and Customer Growth at Planet Labs

May 1, 2021 - April 1, 2022

Developed production APIs in Go deployed on Google Kubernetes Engine; built data pipelines processing millions of daily events. Integrated systems via Google Pub/Sub, Apache Beam, Dataflow, and BigQuery; managed GCP infrastructure and DevOps practices. Contributed to observability stack using DataDog and Google Cloud Logging; served as on-call engineer for production systems.

Software Engineer – Analytics Applications at Planet Labs

February 1, 2020 - May 1, 2021

Designed and deployed Planet's summary statistics API with sub-5-second response times; optimized performance through A/B testing and data-driven iteration. Reduced infrastructure costs by 83% ($20K → $3.5K) through systematic performance optimization and caching strategies. Served as on-call engineer for customer-facing analytics systems; implemented monitoring and troubleshooting for complex distributed environments.

Machine Learning Engineer at Planet Labs

October 1, 2018 - February 1, 2020

Built object detection and semantic segmentation models using Python, TensorFlow, and PyTorch for satellite imagery processing. Developed MLOps infrastructure for model deployment, experiment tracking, and distributed training on cloud infrastructure. Applied prompt engineering techniques and iterative optimization to improve model performance based on production feedback.

Senior Data Scientist (Consulting) at Insight Softmax Consulting

June 1, 2018 - January 1, 2022

Gathered requirements from enterprise clients (BMW, CresTec, Zaro) and translated business needs into deployed ML solutions. Built recommendation systems, forecasting models, and anomaly detection pipelines; integrated with customer data systems and APIs.