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Fernando Soto

@fernandosoto

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MLOps and Agentic AI engineer building scalable, cloud-native AI platforms.

United States

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What I'm looking for

I seek senior roles building scalable, secure MLOps and AI platform solutions, collaborating cross-functionally to productionize LLMs and multi-agent systems.

I am an MLOps and Agentic AI engineer with over 10 years of experience designing, building, and operating cloud-native intelligent systems across AWS, Azure, and GCP. I focus on scalable, observable, and secure AI workflows that bridge data pipelines, inference infrastructure, and product integration.

My work spans Python backend development, model development, full-stack and platform engineering, and production MLOps for agentic and retrieval-augmented systems. I have implemented RAG pipelines, embedding and vector retrieval workflows, multi-agent orchestration (MCP), and CI/CD automation using tools like LangChain, LlamaIndex, FAISS, Pinecone, PyTorch, FastAPI, Kubernetes, Terraform, Jenkins, Argo CD, Prometheus, and OpenTelemetry.

I deliver measurable operational improvements—such as reduced compute through caching and enhanced observability for drift and latency—and I enjoy collaborating with cross-functional teams to integrate LLMs, vector databases, and inference routing into reliable products ready for production.

Experience

Work history, roles, and key accomplishments

MLOps & Agentic AI Engineer

Envion Software

Jul 2023 - Nov 2025 (2 years 4 months)

Designed and deployed RAG pipelines and multi-agent orchestration, integrating OpenAI/Azure/OpenAI/AWS Bedrock and vector stores to enable scalable semantic search and agentic task automation; implemented CI/CD and observability to track drift and latency.

LlamaIndex Faiss Pinecone OpenAI CI CD Prometheus OpenTelemetry

Full-Stack Software & Platform Engineer

Designli

Oct 2020 - May 2023 (2 years 7 months)

Built a multi-cloud AI platform with FastAPI and React, deploying model orchestration and retrieval APIs on Kubernetes with Terraform; implemented caching that reduced compute usage by 30% and monitored SLAs via Prometheus and Grafana.

fastAPI React Terraform Kubernetes AWS Azure Prometheus Grafana

AI/ML Engineer

SumatoSoft

May 2018 - Aug 2020 (2 years 3 months)

Built automated training and evaluation pipelines with Airflow, Spark, and MLFlow, deployed models via SageMaker and TensorFlow Serving, and implemented performance dashboards and drift detection to improve model reliability.

Airflow Spark MLFlow Sagemaker ELK Dynatrace Docker

Software Engineer (Backend & DevOps)

Loanworks

Jul 2017 - Apr 2018 (9 months)

Developed Python RESTful APIs for financial analytics and AI scoring, containerized legacy services, and automated infrastructure provisioning with Terraform and Jenkins to enable blue/green deployments and improved release stability.

Python Flask REST APIs Terraform Jenkins Docker CI CD Blue Green Deployment

Software & Infrastructure Engineer

VXI Global Solutions

May 2015 - Apr 2017 (1 year 11 months)

Developed backend services and ETL pipelines for analytics and ML data preparation, implemented CI/CD with Jenkins, and configured monitoring dashboards to improve observability and operational security with RBAC.

Python ETL Jenkins ELK Grafana CI CD RBAC Data Pipelines Docker

Education

Degrees, certifications, and relevant coursework

Universidad de Dagupan

Bachelor of Computer Science, Computer Science

2011 - 2015

Completed a Bachelor of Computer Science program focused on core computer science topics and practical software development from September 2011 to August 2015.