Jakub Hutko

Senior AI Engineer at Netguru

Designed, implemented, and shipped AI agent workflows for business operations including customer support automation and internal knowledge systems using LangGraph, LangChain Agents, AutoGen, and CrewAI. Built production-grade RAG pipelines combining vector retrieval, hybrid search, reranking, grounding, and structured outputs, significantly reducing hallucinations and improving answer accuracy across enterprise knowledge bases. Established LLM evaluation frameworks with automated benchmarks, regression testing, and qualitative scoring to ensure consistent behavior during model upgrades and provider changes. Operationalized Generative AI systems using MLOps best practices, including model versioning, prompt version control, canary deployments, monitoring, and rollback strategies. Developed scalable AWS-based deployments with secure VPC networking, IAM roles, background workers, and observability tooling, improving system uptime and reducing latency under peak load. Led cross-functional

Senior Data Engineer (AI Integration) at Automattic

Designed and optimized large-scale data pipelines using Apache Spark, SQL, Kafka, and distributed storage, improving data freshness and reliability for analytics and reporting. Implemented streaming ingestion systems for event data and operational metrics, enabling near real-time dashboards and faster incident detection. Integrated AI-assisted data tooling, including LLM-powered metadata search, schema explainers, and automated data quality triage, reducing investigation time for pipeline failures. Improved system observability using ELK-style logging, metrics, and alerting, significantly reducing MTTR. Collaborated with product analytics and engineering teams to define data contracts, KPIs, and reporting pipelines delivered via Power BI and Tableau. Standardized data workflow templates, CI checks, and testing strategies, increasing reliability across distributed data teams. Mentored engineers on Spark performance optimization, partitioning strategies, and streaming best practices.

Senior Software Engineer at GitLab

Delivered high-quality, production-ready web features using React, Next.js, and TypeScript, emphasizing accessibility and maintainable UI patterns. Built GraphQL APIs and Node.js services, improving API consistency and frontend iteration speed. Strengthened CI/CD pipelines with unit and end-to-end testing (Jest, Cypress), reducing regressions and increasing release confidence. Containerized services using Docker and supported deployments on Kubernetes, improving environment parity and developer experience. Optimized MongoDB queries and indexing for high-traffic applications, reducing latency during peak usage.

Backend Engineer (AI / ML / DL) at Nice Cognigy

Developed backend microservices using Java and Spring Boot, delivering robust REST APIs for AI-driven conversational automation platforms. Designed and implemented secure authentication and authorization mechanisms, improving compliance and reducing security risks. Tuned PostgreSQL performance through indexing, query optimization, and schema migrations. Integrated LLM capabilities into backend services, including provider abstraction layers, prompt routing, and structured response handling. Supported Angular-based internal tools for configuration and operational dashboards, improving usability for non-technical users.