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Ivan Stankevichus

Senior Software Developer | Agentic AI Development Enthusiast

✨ About Me

I build AI-native systems where autonomous agents and large language models collaborate with humans to solve complex, real-world problems — blending deep software engineering with AI-first innovation.

I'm an AI Solutions Engineer and Systems Architect with a background in cloud-native software, DevOps automation, and scalable service design. While I've spent years developing production-grade systems with Java, Kotlin, and React.js on platforms like Azure and Kubernetes, my primary focus today is on creating intelligent, self-improving agentic architectures.

🤖 Current Focus: Agent-Based & LLM-Powered Systems

I specialize in building multi-agent AI workflows using Microsoft AutoGen, LangGraph, and OpenAI APIs. I integrate tools like Cursor and GitHub Copilot into engineering pipelines to create adaptive, maintainable, and production-ready AI solutions.

📄 Research & Thought Leadership

I author technical white papers and research-driven blog posts on AI agents, LLM orchestration, and the evolution of AI-augmented development. My work bridges applied AI research and real-world system design.

🛠️ I don't just write code — I architect ecosystems where AI acts as a teammate.

Professional Experience

Siili Solutions

Senior Fullstack Software Developer

January 2025 - Present Joensuu, North Karelia, Finland

Valamis

Senior Software Developer

December 2021 - January 2025 (3 years 2 months) Joensuu, North Karelia, Finland

Cloud-native, k8s orchestrated scalable microservice applications development, Azure Cloud technologies. Enterprise system grade integrations development. Apache Kafka-based data pipeline-driven applications development.
Leading Software Development and Technical Teams in continuous customer oriented Solution Delivery on various international and multi-national projects.

Valamis

Software Developer

March 2020 - December 2021 (1 year 10 months) Joensuu, Eastern Finland, Finland

Valamis

Junior Software Developer

September 2019 - February 2020 (6 months) Joensuu Area, Finland

Valamis

Software Developer Trainee

February 2019 - August 2019 (7 months) Joensuu Area, Finland

Siemens Osakeyhtiö

System Specialist, Software Developer

March 2016 - September 2016 (7 months) Espoo, Southern Finland, Finland

Siemens Osakeyhtiö

Trainee, Customer Services, Software Engineering

May 2015 - March 2016 (11 months) Espoo

Research and development, Cloud services, System Specialist, Full-stack JavaScript web developer

ABB

Software Development Intern, Intelligent Devices

April 2014 - August 2014 (5 months) Ladenburg

Industry 4.0 project, OPC UA, C#

Core Skills

AI Technologies & Tools

TensorFlow Deep Learning Machine Learning HuggingFace RAG LLM Transfer Learning NLP Agentic AI Multi-Agent Systems Microsoft Autogen Cursor Model Context Protocol (MCP) servers LangGraph vLLM

Backend & Platform

Node.js NestJS Next.js Prisma WASM FastMCP FastAPI

Data & Observability

Qdrant Polars Prometheus Grafana Infinity Embedding Engine OTEL

Cloud & DevOps

Azure Azure AI Vertex Kubernetes Docker GCP Azure SQL Database Google Cloud Run Azure Functions

Frontend

React Next.js Redux.js

Databases

MongoDB PostgreSQL Redis Elasticsearch

Projects & Experience

Founder & Builder — AI Tool Orchestration Platform (In Progress)

Designed and built agent-first backend architecture using NestJS and Prisma, enabling multi-agent LLM workflows via REST and protocol-native interfaces (MCP).

Developed semantic tool discovery with hybrid vector search (dense BGE-M3 + sparse SPLADE) in Qdrant, supporting high-recall, filterable retrieval.

Implemented a modular execution system for secure, composable tool workflows, including WASM and LLM-enhanced orchestration.

Orchestrated tool lifecycles (discovery → selection → execution) with LangGraph, enhanced by lightweight vLLM for smart routing and fallback.

Integrated observability and metrics tracking with OTEL and Prometheus-compatible tracing for performance diagnostics.

Built a hybrid embedding pipeline combining FastEmbed and TF-IDF to support RAG and semantic search use cases.

Currently enhancing and improving the codebase to achieve pre-release grade stability, performance, and validation readiness.

NestJS Prisma Multi-Agent Systems LLM MCP Qdrant BGE-M3 SPLADE WASM LangGraph vLLM OTEL Prometheus FastEmbed TF-IDF RAG

Personal R&D Project · 2025 – Present

R&D: Autonomous Multi-Agent AI Trading System (In Progress)

Designed and implemented a multi-agent trading system using LLM-based agents for analytics, trade execution, risk supervision, and sentiment filtering.

Deployed local and cloud LLMs with automatic fallback and latency-aware routing; integrated real-time sentiment analysis using a custom-trained topic classifier on Hugging Face (FinNews Topic Classify).

Built a semantic enrichment pipeline with dense (BGE-M3) and sparse (SPLADE/BM25) embeddings, served via Infinity embedding engine for high-throughput, low-latency vectorization.

Engineered a Polars-powered indicator engine for real-time RSI, SMA, and earnings surprise tracking, generating market context embeddings for retrieval and filtering.

Integrated Qdrant vector database to support hybrid queries over news, market context, and entity metadata; supported filters by symbol, sector, sentiment, and events (e.g., EPS, M&A).

Implemented Prometheus + Grafana observability, tracking token usage, P&L performance, execution latency, and agent loop metrics.

Established automated safety and feedback loops:

  • Risk halting on daily drawdown or LLM failure
  • Backtests with dynamic strategy weighting using reward feedback and multi-agent consensus
Currently validating agent orchestration and retrieval logic in simulated and live market streams, preparing for end-to-end strategy testing.

Multi-Agent Systems LLM Sentiment Analysis Hugging Face BGE-M3 SPLADE BM25 Infinity Embedding Engine Polars Qdrant Prometheus Grafana

Solo Research & Engineering Project | March 2025 – Present

Financial News Topic Classifier (Published on Hugging Face)

Developed a financial topic classifier using transfer learning by adapting the Trading-Hero-LLM (originally trained for sentiment classification) to a new task: multi-topic categorization of financial news.

Froze pretrained layers and fine-tuned classification heads on Kaggle's ZeroShot Financial News dataset covering 20 business topics (e.g., Earnings, Fed, M&A, Commodities).

Engineered the label space and input representation to align with single-label classification and ensure class separation in imbalanced conditions.

Achieved macro F1 > 85% with consistent per-class performance across highly varied financial narratives.

Published the model to Hugging Face, making it usable for news categorization, finance-aware NLP pipelines, and downstream routing/logging in trading systems.

Integrated the classifier into an LLM-agent pipeline for topic-aware trade signal filtering and RAG document tagging.

This project demonstrates practical transfer learning, financial domain adaptation, and open deployment of reusable NLP components.

Hugging Face Transfer Learning NLP Finance Kaggle LLM Agent RAG

Finance NLP Model Development & Transfer Learning | 2025 | huggingface.co/leonas5555/finnews-topic-single-classify

Competence Development Assistant (AI Assistant)

As sole architect and developer, I designed and implemented this competence development assistant using AI-assisted coding techniques. I created the event-driven architecture with an asyncio-based event bus implementing publish/subscribe and request/response patterns. I architected the agent system using Microsoft's Autogen framework, developing SwarmGroupChat functionality with proper handoff between specialized competence development agents. I built a comprehensive component system with registry, factory, and caching mechanisms for extensible management. I implemented the repository pattern for standardized database access across all data models, ensuring consistent handling of development plans and user profiles. I created testing infrastructure including mocks, integration tests, and performance benchmarks.

Microsoft Autogen Cursor OpenAPI Agentic AI Azure AI Prompt Engineering Git Python ChatGPT Prometheus

Internal | March 2025 - April 2025 | Architect/Developer

Cloud Product Solutions: Online Compliance & Accreditation Management (TL)

Played a key role in the end-to-end development, continuous maintenance, enhancement, and technical support of the solution. Acted as the Technical Team Lead for the solution-focused team comprising full-stack developers, QA engineers, and operations staff. Responsibilities included collaborating with customers to plan sprints and project deliverables, scheduling and coordinating team activities, strategizing technical implementation, designing event-driven orchestration and high-availability features, hands-on programming, DevOps pipelines, and Azure Kubernetes components. Led the team to deliver a scalable, high-quality solution while driving technical excellence and ensuring alignment with business objectives.

Spring Boot Elasticsearch Liferay Azure Kotlin OpenAPI Team Leadership Agile Scrum DevOps

Confidential - Global - Legal/Public sector | December 2023 - January 2025 | Technical Team Lead

Cloud Product Solutions: Online Compliance & Accreditation Management (SWD)

Full-Stack Development: Engaged in hands-on programming across both frontend and backend components. Developed and maintained robust microservices, including Java Spring Boot and Kotlin Ktor API services. Implemented Apache Kafka consumers and producers to streamline data processing. Designed and executed efficient data storage and retrieval solutions using PostgreSQL, Elasticsearch and Redis in a microservices environment. Crafted dynamic SSR React.js UI components. Established and configured DevOps pipelines within Azure; managed Azure Kubernetes and platform components using Helm and Terraform.

Spring Boot Functional Programming Liferay Terraform Azure Kotlin OpenAPI React PostgreSQL

Confidential - Global - Legal/Public sector | January 2022 - December 2023 | Senior Software Developer

Cloud Product Solutions: Online Learning Platform Migration

Engineered a seamless transition from Oracle DB to PostgreSQL in Azure SQL by designing and implementing robust data extraction and migration processes. Developed and optimized migration scripts using Docker and Azure-based cloud solutions. Built and maintained DevOps pipelines and Kubernetes Helm charts. Developed a microservice integrating PostgreSQL and Elasticsearch for robust data management and high-performance search. Developed Java Spring Boot microservices and SCIM API to synchronize user HR and learning data from third-party vendors, and created Liferay UI portlets to enhance user experience.

Spring Boot Elasticsearch Liferay Azure Kubernetes Docker PostgreSQL SCIM

Confidential - Global - Travel Industry | June 2021 - December 2021 | Software Developer

Cloud Product Solutions: Global Search

Developed a feature-rich search UI using React.js and Redux, integrating advanced pagination, facets, sorting, dynamic results prompts, and intelligent text suggestions. Engineered scalable Kubernetes backend API microservices that process UI actions and deliver paginated search results directly from the Elasticsearch API. Configured Kubernetes Helm charts to streamline the deployment of related services and SSR UI components.

React Redux.js Elasticsearch Kubernetes Helm TypeScript

Internal Product | June 2019 - October 2019 | Software Developer

Education & Certificates

Education

Bachelor's Degree, Industrial Automation Engineering, Jyväskylä University of Applied Sciences, 2016

Certificates

  • EITCA Artificial Intelligence – EITCA Academy
  • Azure AI Engineering Associate – Microsoft
  • Microsoft Certified: Azure Administrator Associate – Microsoft
  • Microsoft Certified: Azure DevOPS Expert – Microsoft

Languages

  • Russian (native)
  • Finnish (fluent)
  • English (fluent)

© 2024 Ivan Stankevichus. Blog content licensed under CC BY-NC-ND 4.0. Code samples under Apache 2.0.