Samsung Electronics
First: a reliable signal.
I automated voice-recognition tests across phones, Smart TVs and home appliances, from command playback to comparison of the result.

Software automation & AI
I combine Python, integrations and AI to reduce manual work and move from idea to production more efficiently. Over 15 years of engineering experience.
Experience from projects for
Selected professional experience. Intel and Cisco: work delivered on projects for these companies.
Experience
Selected work across electronics, networking and enterprise storage.
Go to services
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Samsung Electronics
I automated voice-recognition tests across phones, Smart TVs and home appliances, from command playback to comparison of the result.
Projects for Intel and Cisco
I built a Python framework for Intel SmartNIC and DPDK validation. For Cisco, I developed gNMI, gRPC and OpenConfig telemetry automation.
Dell Technologies · Principal
I design Data Path I/O test infrastructure using Python/PyTest, NVMe-oF, SPDK and CI, including failure and recovery scenarios.
Dell Technologies · working methods
I introduced Markdown specifications as a shared reference for implementation by engineers and with AI assistance.
Services
Start with the bottleneck in your team’s work. We define the scope around your existing tools and the result you need.
I assess which tasks are worth automating, how systems depend on each other and what implementation may cost.
You receive priorities and a recommendation: build, integrate or buy.
I automate reports, document workflows and data transfers between stages of work.
Outcome: a process that runs on agreed rules and flags exceptions.
I build API connections and tools for tasks that off-the-shelf software does not cover.
The scope includes error handling and documentation for maintenance.
I create automated tests and integrate them into the software build and release process.
The team receives feedback on failures before deploying a change.
I define the roles needed, assess candidates’ technical skills and support onboarding.
Outcome: clear responsibilities and a plan for starting work.
AI in practice
Two uses: AI within your business process, and AI to support software development. Both require the output to be checked.
Documents, tickets and reports: a model extracts information or drafts an output, while Python and APIs route it to the right system.
I use AI for prototyping, implementation and test preparation against an agreed specification. I review the code and architectural decisions.
I define acceptance criteria and check incorrect outputs and exceptions. We agree on monitoring, costs and the points that need human approval.
When explicit rules are enough, I use conventional code. I choose AI models for tasks that require interpreting content.
How I work
I lead the project and own the technical decisions. I handle smaller engagements myself; for larger ones, we build a team around the scope.
We agree on the problem, acceptance criteria, budget and data access.
We test the key assumption on a small sample, giving you evidence for the next investment decision.
We launch the solution, verify it in the target environment and hand over documentation.
We agree who responds to failures, how to monitor the system and which changes take priority.
About me
Principal Software Engineer

I’m Jarek. Before proposing a solution, I want to understand who will use it and what gets in their way today.
You speak directly with the person analysing the problem and writing the code. I explain technical trade-offs, identify constraints and help decide what to tackle now and what can wait.
Let’s start a conversation
Tell me what you do manually today, which tools you use and what you would like to improve.