Gen AI Adoption Lead (Engineering Productivity), N-iX, PL

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 2,000+ 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 Lead (Engineering Productivity) to join our team.

We’re building a small, sharp team to reinvent how software gets built—using GenAI to augment the SDLC end-to-end. You’ll lead by doing: pilot use cases, wire tools into real workflows (CLI/IDE/CI), and teach teams to ship faster with higher quality. No hype—measurable impact.

You will be joining a core, 6-person GenAI Adoption group inside Engineering. We partner directly with delivery teams to make AI a daily habit (coding, tests, reviews, docs, DevOps). Think: Copilot/Claude/Cursor + scripts/agents + CI hooks. We’re remote-first across the EU/EE (PL/UA welcome).

Key Responsibilities:

• Embed AI in the SDLC: turn “nice demo” into daily CLI/IDE workflows and CI steps.
• Run fast pilots: pick 2–3 high-ROI use cases per account, ship in weeks, measure, scale.
• Build glue + agents: small tools, prompts, and automations that actually stick.
• Coach by pairing: live code-along, short playbooks, internal demos.
• Measure outcomes: baseline → deltas (cycle time, PR throughput, defects, time saved).
• Keep it safe: model/provider choices, data handling, guardrails, policy basics.

Requirements:

• 5+ years as hands-on engineer (Java or .NET great; Python/TS welcome).
• Daily driver of GenAI coding tools (Copilot, Claude Code, Cursor, Code LLMs).
• Comfort with CLI/IDEs/CI (GitHub/GitLab, JetBrains, VS Code, Bash), and wiring APIs.
• You’ve shipped at least one AI-assisted workflow (tests, codegen, review bot, docs).
• You can teach: workshops, pairing, short guides. Clear English, straight talk.
• Pragmatic about quality & security (you know when AI output is not production-ready).
• Bonus: AWS/Azure, Kubernetes/Terraform, prompt patterns, lightweight agent orchestration.

You may not like the role if:

• You prefer slideware over shipping.
• You avoid terminals and CI—this is engineer-first, not tool theater.
• You want certainty. We iterate, measure, and change course fast.