Senior Software Engineer · Motorola Solutions

Dawid
Ziniewicz.

I build test automation that scales and AI agents that think — turning 4+ years of telecom-grade QA into intelligent tools that make software quality faster and smarter.

Get in touch View experience
Kraków, Poland 4+ years experience Python · C++ · LLMs
Portrait of Dawid Ziniewicz
Now buildingLangflow release & test‑gen pipeline
CertifiedAI_Devs 4 · GenAI & LLMs
01 About

Engineering where quality assurance meets artificial intelligence.

I'm a Senior Software Engineer in Kraków with a background in Biomedical Engineering and a habit of automating everything I touch.

For over four years I've built automated testing frameworks for telecom-grade and mission-critical systems — first on LTE/NR protocol stacks at Nokia, now at Motorola Solutions, where I was promoted to Senior in September 2026.

Today my focus is applied AI: I lead an AI-agent initiative that reads customer-reported defects and recommends the most effective test cases to validate a fix, deploy automated AI pipelines in Langflow and n8n, and build API servers that open our test framework up to automation and agents. Right now I'm building a Langflow pipeline that flags what's new in each release and which features are ready for testing — and writes black-box system and GUI tests automatically. I work with deep learning, Large Language Models and Generative AI, and I'm AI_Devs certified in building LLM-powered applications.

I care about tools people actually use — fast feedback loops, clean CI/CD, and automation that gives engineers time back.

Dawid Ziniewicz smiling
~/krakow · PL
4+
Years in software & test automation
2
Global tech companies — Nokia & Motorola Solutions
C1
English proficiency — Polish native
02 Experience

Where I've built things.

From 3GPP-compliant protocol testing to LLM-driven quality tooling — always close to the systems that can't afford to fail.

Motorola Solutions Systems
Kraków, Poland
Feb 2025 — Present

Senior Software Engineer — Test Automation

Sep 2026 — Present ● Current

Software Engineer — Test Automation

Feb 2025 — Sep 2026
  • Spearheading an AI agent project that analyzes customer-reported defects and automatically recommends the most effective manual test cases for validation — optimizing the bug-fixing lifecycle.
  • Designing and deploying AI systems and automated AI pipelines in Langflow and n8n — orchestrating LLM workflows that take repetitive work off engineers' plates.
  • Writing AI agents and building API servers for our in-house test framework, so tests, data and AI tooling can be integrated and driven programmatically.
  • Applying deep learning techniques to improve data analysis within the internal testing application.
  • Developing and optimizing automated black-box test scripts in Python and Groovy to analyze large datasets and validate system stability.
  • Engineering internal productivity tools in Python that streamline daily workflows and boost team efficiency.
  • Setting up laboratory hardware — configuring PCs for new system requirements and managing network connectivity for a stable test environment.
  • Working in an Agile/Scrum team with JIRA for defect tracking and Git for version control.
PythonGroovyLLM AgentsLangflown8nAPI serversDeep LearningBlack-box TestingJIRAGit
Nokia Solutions and Networks
Kraków, Poland
Jul 2022 — Feb 2025

Software Engineer — Test Automation (Robot Framework)

  • Developed and executed automated test cases for the L3 LTE layer, ensuring full compliance with 3GPP protocol standards.
  • Designed and implemented Jenkins CI/CD pipelines to automate black-box test execution with rapid feedback loops.
  • Built and maintained C++ and Python testing libraries for eNB (Evolved Node B) simulators.
  • Conducted rigorous automated black-box testing on NR/LTE technologies to verify functionality and performance.
  • Engineered in-house tools that improved testing productivity and streamlined defect reporting.
  • Explored emerging technologies — including 6G and Large Language Models — to shape future test strategies.
Robot FrameworkPythonC++JenkinsLTE / NR3GPP
03 Featured work

AI agents & pipelines for smarter quality.

Customer-reported defects arrive messy and under time pressure. The flagship agent I lead at Motorola Solutions reads each report, understands its context and recommends the manual test cases most likely to validate the fix — so engineers spend less time searching and more time fixing.

  1. Defect report

    A customer-reported issue lands in the tracker.

  2. AI analysis

    An LLM-based agent extracts symptoms, scope and context.

  3. Test matching

    Candidate cases are scored against the test library.

  4. Recommendation

    The most effective manual tests are proposed.

  5. Faster fix

    Validation starts sooner — a shorter bug-fix lifecycle.
Now building

A Langflow pipeline — from release changes to ready-to-run tests.

Release intelligence

Automatic notifications about what's new in the latest releases and which feature initiatives are complete and ready for testing.

Automated black-box test writing

Generating system-level and GUI black-box tests automatically, built on our in-house test framework and the data already available.

AI pipelines

Designing and deploying automated LLM workflows in Langflow and n8n — from prototype to a pipeline the team relies on.

Custom AI agents

Writing LLM agents that work through defect reports and test data and hand engineers actionable recommendations.

API servers for testing

Standing up API servers for our in-house test framework, so tests and results can be driven by tools, pipelines and agents.

LLMsAI AgentsDeep LearningLangflown8nREST APIsPythonDefect Triage
04 Side projects

Yacht Logbook — a sailing logbook in your pocket.

Sailing is how I recharge, so I built the tool I wanted on board. Yacht Logbook is a free electronic sailing logbook that runs in the browser and on phones — designed, built and published by me.

  • Hourly log entries — course, speed, log, wind and sea state, with reminders
  • GPS position & track plus marine weather, tides and a weather map
  • Watch schedule, crew list and cruise references exported to PDF
  • Offline-first & private — no account, data stays on the device
Web appAndroidiOSOffline-firstPL / ENFree
Visit yachtlogbook.org
Homelab

My own little data center — self-hosted and maintained at home.

A playground for infrastructure: I virtualize, host, store and automate on my own hardware — the same hands-on server and networking skills I use in the test lab every day.

  • Proxmox VEVirtualization host · VMs & containers
  • WordPress serverSelf-hosted web server
  • OpenMediaVaultNAS · storage & backups
  • Home AssistantHome automation
  • VPNSecure remote access
05 Expertise

Tools of the trade.

A toolkit shaped by years of test engineering and a growing focus on applied machine learning.

Applied AI & Machine Learning

Designing LLM-powered agents, automated AI pipelines and deep learning models that solve real engineering problems — from defect triage to biomedical image classification.

LLMsAI AgentsGenerative AIDeep LearningOpenAI APILangChainLangflown8nAI pipelinesRAGPrompt Engineering

Test Automation

Frameworks, black-box suites and CI pipelines that give fast, trustworthy feedback.

Robot FrameworkPytestSeleniumPlaywrightBlack-boxGUI testingAI test generation

Programming

PythonC / C++GroovyElixirMatlab

Telecommunication

LTE / NR3GPPL3 protocolseNB simulators

CI/CD & Tooling

JenkinsGitGitLabGitHubJIRALabVIEWAgile / Scrum

Platforms & Infrastructure

LinuxWindowsmacOSAPI serversServer administrationProxmoxOpenMediaVaultHome AssistantVPNLab hardware & networking3D modeling
06 Education & certification

Always learning.

Certificate2026

AI_Devs 4

Generative AI & LLMs in production

Intensive course on integrating Generative AI and Large Language Models into real applications — OpenAI API, LangChain, Retrieval-Augmented Generation and Prompt Engineering. The foundation behind the agents I build today.

Verify credential
Education2019 — 2023

B.Sc. Eng. in Biomedical Engineering

AGH University of Kraków
  • Thesis: developed a deep learning model for the classification of Optical Coherence Tomography (OCT) images in Python.
  • Implemented neural network architectures and performed advanced preprocessing of complex biomedical imaging data.
Languages
  • Polish Native
  • English C1
Beyond the keyboard
⛵Sailing 🧗Rock climbing 🪨Bouldering 🪁Kitesurfing 🚴Cycling 🏃Running 🥾Hiking 🚣Rowing ⛷️Skiing ⛸️Ice skating
07 Contact

Let's build something intelligent.

Open to conversations about AI engineering, test automation and applied machine learning. I usually reply fast.

Say hello
Emaildawidziniewicz@gmail.com
Phone+48 517 382 997
LinkedInin/ziniewicz-dawid