mapping the client's current SDLC and identifying areas with the highest ROI for automation;
defining practices (e.g., analysis, architecture, code standards, testing, release) that should produce repeatable results, not just perform steps;
designing policies: permissible AI uses, control levels, approval workflow, required artifacts and evidence;
embedding security, privacy, quality, and auditability requirements into practices;
integration with tools (ALM, repo, CI/CD, documentation, ITSM, IAM – depending on the environment);
tailoring practices to the organizational context (roles, teams, system criticality, regulations);
workshops, training, and role onboarding (architects, dev leads, QA, security, PO);
support in launching the first use cases and scaling to additional teams;

7+ years of experience in solution architecture / enterprise architecture / lead technical roles in enterprise environments;
Ability to develop governance (standards, decision-making processes, quality control, risk, accountability);
Excellent knowledge of SDLC and engineering practices;
Experience integrating solutions in a complex landscape (API, integrations, platforms, IAM);
Excellent communication skills: working with IT, security, compliance, and business; ability to lead workshops;
Fluent in Polish and English, comfortable working with clients and documentation.
You understand how LLM/agentic workflows work, the risks (hallucinations, data leakage, prompt injection) and how to control them through processes
You can design a practice to keep AI on track: context, standards, acceptance criteria, validation.

AI Architect

Winged IT