Gen AI Adoption Lead – Java Engineering Focus

N-iX is a global company with Ukrainian roots that helps businesses across the world develop successful software products. Founded in 2002 N-iX has come a long way and increased its presence in nine countries spanning Europe the US and Latin America. Today we are a strong community of 2000 professionals and a reliable partner for global industry leaders and Fortune 500 companies. We are committed to continuous innovation and are now strategically leveraging Generative AI to significantly enhance our Software Development Life Cycle (SDLC) productivity.

We are looking for a skilled Gen AI Adoption Leadto join our team.

The Gen AI Adoption Lead will join a specialized team of technical leaders driving N-iXs transformation toward AI-augmented software development. Each lead is assigned to strategic projects across the organization combining hands-on technical implementation with leadership to achieve measurable productivity improvements. You will take a leading role in identifying critical use cases expertly guiding teams on the selection and implementation of specific Gen AI tools and engineering approaches providing mentorship and technical direction and spearheading the scaling of successful Gen AI integrations throughout the company. Your success will be measured by tangible improvements in development efficiency code quality and overall engineering team empowerment.

Key Responsibilities:

• Strategic GenAI Opportunity Identification: Lead the collaborative effort with software development teams to pinpoint strategic engineering workflows within the SDLC where Generative AI can deliver substantial and scalable productivity gains.
• Expert Tool & Technical Direction: Provide expert guidance and technical direction to engineering teams on the evaluation selection and optimal application of relevant Gen AI tools and engineering methodologies.
• Mentorship & Engineering Enablement: Mentor and technically enable engineering teams through comprehensive education hands-on coaching and the development of best practices for Gen AI adoption.
• Technical Implementation Leadership: Provide strong technical leadership and guidance to engineering teams during the design implementation and integration phases of Gen AI solutions ensuring adherence to architectural standards and best practices.
• Driving Scalable GenAI Solutions & Best Practices: Architect and champion the development and adoption of robust best practices for the secure effective and scalable integration of Gen AI within the SDLC across N-iX engineering.
• Create data-driven case studies with hard metrics (story points cycle time defect rates) that prove ROI to executives and clients.

Requirements:

• Deep understanding of the Software Development Life Cycle (SDLC) and extensive practical experience leading technical efforts across various development workflows.
• Extensive and demonstrable experience as a Lead Java developer with a deep understanding of software architecture design patterns and best practices in software development.
• Direct hands-on experience leading the implementation of specific Gen AI tools relevant to software development within engineering teams (e.g. GitHub Copilot Cursor AI-powered testing frameworks).
• Significant experience leading and mentoring technical teams in the adoption of new technologies.
• Exceptional communication collaboration and influencing skills with the ability to effectively convey complex technical visions to both technical and non-technical stakeholders and drive adoption.
• Extensive experience with Agile/Scrum methodologies and a proven track record of leading technical teams within these frameworks.
• Strong analytical and strategic thinking skills with a data-driven approach to evaluating the impact and ROI of technology initiatives.
• Proven ability to measure and document productivity improvements through controlled experimentation.
• English level - Upper-Intermediate or higher.

Nice to Have:

• Experience in developing and delivering technical leadership training programs and workshops for engineering teams.

What Youll Actually Do:

• Hands-On Development (60%): Join priority projects for 3-6 month assignments becoming a true team member who codes daily alongside developers.
• Impact Measurement & Validation (20%): Track metrics over full sprints and releases - real productivity gains only show after developers overcome the 11-week AI learning curve. Build trust through consistent presence.
• Internal Knowledge Sharing & Enablement (20%): While embedded in one project run weekly AI Coffee Chats for other teams. Document patterns that work and share asynchronously. Full workshop rollouts happen only after proving 3 month results.
• Real example: Spend 6 months with one project achieve substantial velocity increase then transition gradually while maintaining office hours. No helicopter consulting.

Were NOT Looking For

• Architects who only draw diagrams
• Consultants who only make presentations
• People who talk about AI but dont use it daily