Technical leadership
Senior leadership for delivery teams: architecture decisions, estimation, prioritization, and accountability for outcomes.
- Architecture & estimation
- Delivery ownership
- Stakeholder alignment
I help organizations design, build, stabilize, and scale business-critical systems — and introduce AI-assisted development with the engineering discipline it requires.
Currently building the foundations of software development teams for BMW via Achala Sulzer.
Most enterprise software does not fail on syntax. It fails on unclear specifications, weak ownership, fragile production paths, and teams that have not been built to deliver. That is the work.
Specification, architecture, estimation, and implementation of business-critical software — owned end to end.
Incident analysis and structural remediation for complex applications under production pressure.
Introducing AI into delivery with the specs, guardrails, reviews, and testing enterprise systems require.
Before becoming a software engineer, I served as a naval and merchant navy officer on some of the largest vessels in the world, including Emma-class container vessels and VLCC tankers.
In that environment, decisions affect the vessel, the cargo, the crew, your teammates, and the safety of the operation. There is no room for performative leadership.
I lead by example. Positive leadership — clarity, trust, preparation, accountability — is consistently stronger than management by fear, especially when the stakes are real.
The same operational disciplines now apply to enterprise software delivery.
Engagement led via Achala Sulzer. Focus on team structure, engineering standards, delivery cadence, and the technical groundwork required for sustained enterprise output.
Roles, ownership boundaries, hiring signals, onboarding paths.
Code review, branching, CI/CD, definition of done, quality gates.
Planning, estimation, forecasting, dependency management.
Architecture, environments, observability, release discipline.
Used well, AI compresses delivery without compromising quality. Used carelessly, it produces plausible code that fails under enterprise conditions. The difference is method.
AI works against a stated specification, not a vague intent.
Constraints, conventions, and architectural boundaries are explicit.
Generated code is reviewed with the same rigor as human-authored code.
Behavior is verified through tests, not by visual inspection of output.
Decisions, prompts, and changes are auditable.
Observability, error handling, and rollback are part of the work.
A personal product initiative for engineering team management. Built using the same method I bring to client engagements: explicit specifications, AI-assisted implementation under review, and production validation.
Tooling for engineering managers to track delivery health across teams.
Specification-led; AI used inside guardrails; reviews and tests gate merges.
Java, Spring Boot, Angular, AWS.
Evidence that the delivery approach scales beyond a single client.
Each engagement is scoped to the problem in front of the organization, not packaged into fixed deliverables.
Senior leadership for delivery teams: architecture decisions, estimation, prioritization, and accountability for outcomes.
Building the structural basis for new software teams: roles, standards, onboarding, and engineering practice.
Introducing AI-assisted development into existing teams with the specs, reviews, and guardrails enterprise systems require.
Root-cause analysis for complex applications under production pressure — read the failure, isolate the structural cause, restore confidence.
Structural remediation programs that move a system from firefighting to predictable operation, with sequenced optimisation thereafter.
Calm, organized leadership for high-stakes environments — decisions, coordination, and trust under pressure.
Engagements selected for relevance to enterprise technical leadership and operational discipline.
Building the foundations of software development teams. End-to-end design and implementation of web solutions for the automotive sector — logistics, planning, forecasting, data visualization. Establishing engineering standards, delivery cadence, and architectural groundwork.
My own consultancy company. B2B engagements covering design, implementation, estimation, and per-hour technical consulting for enterprise software delivery.
Designed microservices supporting real-time credit scoring and application workflows. CI/CD with Maven and Jenkins on Java 11 / Spring Boot / Angular.
Next-generation platform for medical and radiology clinics in the US.
Internal administration application for printing sites, distribution, and reporting. FT SSO integration; Kubernetes deployment. Java 11, Spring Boot, Neo4j.
Event-driven microservices for an EU banking regulator validating market transactions against pre-defined rule sets.
Internal ERP system covering planning, finance, and time management. Spring, Hibernate, AngularJS, AWS.
Proprietary software products and consultancy for energy trading platforms (Endur ecosystem). Java EE, Spring Boot, Oracle.
Market research surveys on IBM SPSS Dimensions (mrScriptBasic). Deployment, QA, client support, and data delivery.
Operational leadership in high-stakes maritime environments. Decisions affecting vessel, cargo, crew, and the safety of the operation. MSc in Marine Navigation, 2004.
Leadership shaped in high-stakes maritime operations before software — not learned from a management book.
AI used inside a disciplined engineering method — specifications, reviews, tests, production validation.
Comfortable owning complex applications under production pressure and bringing them back to stability.
Capable of taking the correct decision when the picture is partial — and following through with disciplined corrective actions as new information emerges.
Senior technical leader and full-stack software engineer based in Sofia, Bulgaria. Work spans specification, architecture, estimation, implementation, incident resolution, and team leadership.
Engineering depth in Java, Spring Boot, Quarkus, Angular, AWS, and enterprise data flows. Practical depth in planning, forecasting, logistics, and AI-assisted development.
Earlier career as a naval and merchant navy officer on Emma-class container vessels and VLCC tankers — the source of a leadership style built on responsibility, preparation, and trust under pressure.
Initial conversations are direct and specific. Bring the problem, the constraints, and the people involved — we can move quickly from there.