AI-Driven SDLC Transformation & Developer Productivity Platform
Key Expertise
Experience
12+ years
Timezone
CET (UTC +1)
Skills
AI / ML
Languages
Databases
Infrastructure
Frameworks
Integrations & Protocols
Overview
Led an AI-first transformation of the software development lifecycle for a charity and volunteering platform serving enterprise clients. The initiative encompassed driving AI code-generation adoption across the engineering team, building AI-powered internal tooling integrated into sprint workflows, implementing MCP servers for streamlined AI-assisted development, and constructing a RAG-powered knowledge base to surface institutional knowledge at scale. The project spanned full-cycle development including requirements, architecture, security, and policy integrations using an AI-first approach.
Achievements
Drove AI code-generation adoption from 23% to 77% across the engineering team within 5 months. Reduced team onboarding time from 3 weeks to 1 week by building a structured project knowledge base with AI use-case guides. Decreased repetitive engineering work by 56% through custom AI-powered tooling. Raised team AI trust score from 2 to 4 out of 5 through hands-on knowledge-sharing sessions. Reduced time-to-delivery from approximately 1 month to 2 weeks through streamlined CI/CD and AI-assisted code review.
Responsibilities
- Designed and executed a structured SDLC transformation strategy, driving measurable AI adoption metrics across the engineering team within a 5-month timeline.
- Built AI-powered internal tooling: a Spring Microservice Factory for automated service scaffolding and an AI-assisted test-case generator integrated directly into sprint workflows.
- Implemented MCP servers to streamline AI-assisted development; integrated LangChain4j, Koog, and SpringAI into production services for agentic capabilities.
- Built an AI-powered internal knowledge base with RAG architecture to surface institutional knowledge at scale, cutting onboarding time by 66%.
- Led full-cycle development (requirements, architecture, security, policy integrations) using AI-first approach with Cursor and Claude Code.
- Designed AWS-native architecture; executed ETL migration of legacy codebase and data to modern stack including Flyway-managed database migrations.
- Conducted hands-on knowledge-sharing sessions on AI agents and agentic solutions; collaborated with distributed teams across Canada, Spain, and Romania.
Technologies Used
Key Expertise
Experience
12+ years
Timezone
CET (UTC +1)
Skills
AI / ML
Languages
Databases
Infrastructure
Frameworks
Integrations & Protocols
This project was delivered by
Oleksandr S.
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