Senior AI Platform Engineer

<p><strong><span data-highlighted="true" data-vc="highlighted-text">N-iX</span></strong> is a global software development company founded in 2002, connecting over 2,400+ tech professionals across 40+ countries. We deliver innovative technology solutions in cloud computing, data analytics, AI, embedded software,<span data-highlighted="true" data-vc="highlighted-text">IoT</span>, and more to global industry leaders and Fortune 500 companies. Join us to create technology that drives real change for businesses and people across the world.</p> <p><strong>Our client</strong> is a fast-growing European fintech company in the business spend management space — corporate cards and related financial products — serving SME and mid-sized business customers across the EU and UK, in a regulated environment with GDPR compliance obligations. Engineering is organized into cross-functional squads, with platform/enabling teams providing shared tooling horizontally. The client already runs an AI-native engineering practice: Claude Code and GitHub Copilot are used daily, supported by a growing library of shared, versioned Skills embedded in key repositories, enabling an end-to-end flow from ticket to implementation, testing and PR in several codebases. AI tool/connector rollout follows an approved-list and pilot process. The client is AWS-first overall; for data platform and analytics workloads it also runs GCP, with BigQuery as the primary data warehouse. Day-to-day coordination is Slack-first, with Linear for ticket tracking, GitHub for code/PR review, and Notion as the knowledge base.</p> <p>The client is also building out its AI platform and agentic capabilities: it recently launched an MCP surface in closed beta, giving external AI assistants a structured way to connect and perform real workflows behind guardrails, and treats agent reliability as a system property (tool contracts, approval/consent gates for write actions, evaluation harnesses).</p> <p>We're looking for <strong>a Senior AI Platform Enginee</strong>r to design, build and operate the shared GenAI infrastructure that product teams rely on.</p> <p><strong>Key Responsibilities:</strong></p> <ul> <li>Design, build and operate shared GenAI infrastructure: LLM routing, vector search and RAG infrastructure, MCP gateway, and AI observability/evaluation tooling.</li> <li>Apply strong distributed-systems fundamentals: async workflows, idempotency, failure design.</li> <li>Work hands-on with LLM APIs in production.</li> <li>Apply an AI-security mindset: prompt injection defenses, PII-in-logs handling, credential handling.</li> <li>Apply real engineering rigor to the Context Development Lifecycle (CDLC): generate, evaluate, distribute and observe the context that powers AI agents.</li> <li>Multiply the output and quality of the squad you join, and share patterns/practice beyond your immediate team so adoption compounds across the organisation.</li> <li>Embed directly into a client squad as a hands-on Individual Contributor (not a coaching/managerial role).</li> </ul> <p><strong>Must-Have Skills:</strong></p> <ul> <li>Kotlin or Python as primary proficiency, with comfort contributing to both.</li> <li>Experience designing/building/operating shared GenAI infrastructure: LLM routing; vector search and RAG infrastructure; MCP gateway; AI observability and evaluation tooling.</li> <li>Strong distributed-systems fundamentals: async workflows, idempotency, failure design.</li> <li>Hands-on production experience with LLM APIs.</li> <li>AI-security mindset: prompt injection, PII in logs, credential handling.</li> <li>Agent &amp; harness engineering fluency, with concrete evidence of building/operating this kind of tooling, not just using it.</li> <li>Comfortable with the client's current daily tools: Claude Code and GitHub Copilot.</li> </ul> <p><strong>Nice-to-Have Skills:</strong></p> <ul> <li>Specific cloud depth (AWS and/or GCP), Grafana, or named LLM API vendors. The RFP describes these capabilities generically rather than naming specific tools for this role — listed here as plausible, not confirmed.</li> </ul><div class="content-conclusion"><p><strong>We offer*:</strong></p> <ul> <li>Flexible working format - remote, office-based or flexible</li> <li>A competitive salary and good compensation package</li> <li>Personalized career growth</li> <li>Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)</li> <li>Active tech communities with regular knowledge sharing</li> <li>Education reimbursement</li> <li>Memorable anniversary presents</li> <li>Corporate events and team buildings</li> <li>Other location-specific benefits</li> </ul> <p>*not applicable for freelancers</p></div>