Open to opportunities

Diman Kurtev

@dimankurtev

Message

I build production AI agents, RAG systems, and reliable MLOps platforms.

Bulgaria

Message

At John Deere, I build production AI applications, RAG services, and agentic workflows that reduce manual operational effort by 30–40% and serve 2K+ internal users. I integrate Amazon Bedrock, OpenAI, Anthropic, and Gemini with enterprise APIs and knowledge bases using grounding, guardrails, RBAC, audit trails, and evaluation suites.

Across ArgoStack, SofiaAI, and DeepData Labs, I’ve built cloud-native AI platforms, ML pipelines, backend services, and event-driven data systems processing millions of events per day. I turn prototypes into maintainable systems with Python, FastAPI, React, AWS, Kubernetes, Terraform, observability, automated testing, and secure delivery practices.

Experience

Work history, roles, and key accomplishments

Current

Senior AI Engineer

Current

John Deere

Oct 2023 - Present (2 years 10 months)

Design and deliver production AI applications, RAG services, and agentic workflows using Python/FastAPI, Node.js, React, and cloud-native APIs, reducing manual operational effort by 30-40%. Built document and operational-data pipelines covering ingestion, chunking, embeddings, vector search, retrieval logic, reranking, and grounded response generation for semantic search and AI assistants.

Python fastAPI Node React OpenAI Anthropic Gemini RAG Vector Search Kubernetes Terraform CI CD AWS Sagemaker Microservices Event Driven Architecture

AI Platform Engineer

ArgoStack

Aug 2020 - Sep 2023 (3 years 1 month)

Built cloud-native AI and developer platforms using Python, Node.js, Go, React, PostgreSQL, and Redis, exposing reliable REST APIs and real-time interfaces for production SaaS workloads. Integrated AI-driven anomaly detection, assistants, and workflow automation with internal APIs and event-driven services, giving product and engineering teams faster operational insights.

Python Node Go React PostgreSQL Redis REST APIs PyTorch Hugging Face ML Pipelines CI CD Observability Docker Kubernetes

Machine Learning & AI Software Engineer

SofiaAI

May 2018 - Jul 2020 (2 years 2 months)

Developed secure AI-enabled applications and backend services using Python, .NET Core, JavaScript/TypeScript, REST APIs, relational databases, and cloud infrastructure. Integrated prediction, scoring, and recommendation models into business workflows with input validation, fallback logic, model monitoring, and explainable output for enterprise users.

Python .NET Core JavaScript TypeScript REST APIs SQL Cloud Infrastructure Model Monitoring Data Pipelines Docker CI CD

Data & ML Engineer

DeepData Labs

Jul 2014 - May 2018 (3 years 10 months)

Built high-volume ingestion services and data-processing APIs using Node.js, TypeScript, Python, MongoDB, and Kafka, processing millions of events per day. Designed event-driven pipelines powering predictive analytics, segmentation, dashboards, alerting, and downstream machine-learning workflows.