Systems advisory and technical leadership

Systems architect and engineering executive

Sixteen years of software development, including six years leading technical strategy and architecture. Former Head of Software, partnering with scaleup founders and CTOs to adopt verified AI SDLC standards, eliminate delivery friction, and scale organizations without corporate slowdown.

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Products and tools

Active product development

Working software built to solve real engineering problems, tested in production developer workflows.

DEVELOPER TOOL // RUNRAY
LIVE

RunRay

Local-first Chrome DevTools for autonomous coding agents

An offline execution waterfall and diagnostic profiler for autonomous coding agents. It auto-discovers local session logs from Claude Code and OpenCode, attributes spend to individual prompt turns, pinpoints prompt cache breaks, and suggests copyable remediation rules. Runs on localhost with zero network egress.

npx runray view Local execution waterfall Zero network egress Claude Code & OpenCode MIT open source
View repository on GitHub
METHODOLOGY // AI SDLC
DOCUMENTED SPEC

Spec-driven agentic delivery

Multi-agent verification pipeline

A specification-driven code generation pipeline compatible with Claude Code, Antigravity, and OpenCode. It programmatically enforces Clean Architecture, Domain-Driven Design boundaries, and test requirements before code merges.

Claude Code and Antigravity OpenCode compatible Domain boundary checks Automated test gates
Track record

Work and impact

Operational results measured in team velocity, system reliability, and revenue growth.

Engineering organization scaling and silo elimination

Department reorganization and multi-product alignment
TKH Technology
The challenge

Rapid growth required scaling a 30-person engineering department across web, mobile, and IoT without creating delivery bottlenecks.

Leadership action

Doubled the department to 60+ engineers, created autonomous teams governed by OKRs, instituted continuous product discovery, and consolidated technology stacks to .NET, React, and Flutter.

Business impact

Reduced developer onboarding time, established dedicated AI and IoT business units, and helped secure major enterprise accounts.

Enterprise AI SDLC and commercial service line

Organizational AI governance and multi-agent systems
Future Processing
The challenge

Enterprise clients wanted to adopt AI-assisted software delivery but lacked standards to prevent security vulnerabilities, intellectual property exposure, and code decay.

Leadership action

Co-designed organizational AI SDLC standards, led a team of Solutions Architects, and built internal multi-agent tools including a staffing optimization system.

Business impact

Partnered with sales and delivery leaders to launch AI-augmented engineering as a commercial service line, opening new enterprise revenue streams.

Financial compliance platform and fivefold capacity scaling

RegTech architecture on Microsoft Azure
PwC
The challenge

A high-stakes KYC and AML compliance platform needed to multiply delivery capacity quickly while meeting strict audit and security regulations.

Leadership action

Re-architected the core platform into CQRS and DDD microservices on Azure, integrated machine learning classification services, and automated security verification checks.

Business impact

Expanded engineering throughput from 1 to 5 parallel delivery streams with 35+ developers, with zero architectural regressions.

Engineering principles

Core principles

Convictions refined across sixteen years of building cloud systems and managing engineering teams.

PRINCIPLE 01 // FOCUS

Value first, technology second

Software architecture exists to serve business outcomes. I measure engineering success by cycle time, system reliability, and return on investment, rather than industry trends.

PRINCIPLE 02 // VELOCITY

Autonomy over bureaucracy

Process overhead slows teams down. I build autonomous engineering teams with clear ownership boundaries, transparent goals, and strong architectural guardrails.

PRINCIPLE 03 // RIGOR

Verifiable AI adoption

AI tools in software engineering must be verifiable. I build systems that validate generated code against domain rules, type systems, and automated tests before it reaches production.

Contact

Start a conversation

Direct contact for executive technology leadership, systems architecture advisory, or peer connection.

// ADVISORY AND LEADERSHIP

Systems and AI advisory

Direct inquiry for enterprise AI SDLC standards, engineering organization design, cloud architecture audits, or executive technology advisory.

krzysztof@lempka.pl
// PROFESSIONAL NETWORK

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