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操作画面は日本語です。企業が掲載した求人の職種名や説明文は原文のまま表示され、英語の場合があります。

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(Senior) AI Solutions Engineer - Remote (Europe/Asia)

AKTOR Group

リモート勤務

勤務地
Remote (Greece)
勤務時間
Full Time
掲載日
2026年10月17日

応募する前に、企業のウェブサイトで現在も募集中かどうかと詳しい条件を確認してください。

仕事内容

操作画面は日本語です。企業が掲載した求人の職種名や説明文は原文のまま表示され、英語の場合があります。

Aktor Group of Companiesis a leading player in Greece's infrastructure sector, delivering high-end services across Construction, Real Estate, Renewables, Facility Management, and Equity Participations. With 6,100 employees, we build the infrastructure that empowers people and communities to thrive. Aktor AI () is our technology arm, building the next generation of enterprise AI. We deploy fully-managed AI employees that self-train on organisational processes and reach 95%+ accuracy within days. Our agents handle finance operations, contract management, support workflows, and more, with built-in supervision that audits decisions, escalates uncertainty, and learns continuously. We don't sell software licences. We deliver outcomes. We are hiring a (Senior) AI Solutions Engineer to join our AI engineering team remotely and help us build, harden, and scale these agents. The Role This is a hands-on engineering role at the frontier of AI-augmented software development. You will design, build, and ship production AI agents, but the way you build them may look different from what you're used to. Our engineers work heavily with AI coding assistants and autonomous agent tooling. The craft has shifted: writing every line yourself matters less than knowing what good looks like. Making sound architectural decisions, maintaining quality standards, and steering AI-generated output toward well-structured, maintainable systems. You will spend more time thinking, reviewing, and deciding than typing. That said, you still need strong engineering fundamentals. You can't evaluate what you don't understand. The best engineers in this new paradigm are the ones who know when the AI is wrong and can articulate why. What You'll Do Build and ship AI agents end-to-end: from scoping and prototyping through optimisation and production rollout. Architect for reliability: design observability, logging, guardrails, evaluation pipelines, cost controls, and human-in-the-loop flows. Integrate with enterprise systems: build connectors and retrieval pipelines to data stores, APIs, and line-of-business applications. Review and elevate: review AI-generated code and designs with a critical eye. Challenge what doesn't meet the bar, accept what does. Own quality: write and maintain evaluation datasets, define accuracy targets, and treat failure modes as first-class engineering concerns. Document clearly: produce designs, runbooks, and technical documentation that others can follow. What We're Looking For Engineering Judgment Over Stack Knowledge We care far less about which specific frameworks you've used and far more about whether you make good decisions. Technologies change fast; judgment compounds. Strong software engineering fundamentals. You understand how systems are built, how they break, and how to keep them simple. Experience with LLM-based systems in production or near-production settings (agents, RAG, automation, orchestration). A product-minded approach. You think about what you're building and why, not just how. You understand that the goal is a working solution that serves a business need. Architectural taste. You can look at a system design, whether you wrote it or an AI generated it, and tell whether it's sound, over-engineered, or cutting corners that will cost you later. Comfort with ambiguity. AI systems don't behave like deterministic code. You're comfortable with probabilistic outputs, evaluation-driven development, and iterative refinement. Levels Engineer (typically 2–5 years total; 1+ with AI systems) Ships features and integrations independently. Implements evaluation datasets, prompt engineering, and observability. Contributes to design discussions and follows established guidelines. Senior Engineer(typically 6–10+ years; 2+ leading AI deliveries) Leads end-to-end implementations and makes architecture choices. Designs data/retrieval schemas, instrumentation, and cost/latency budgets. Sets quality bars and mentors teammates. Nice to Have Experience with agent orchestration frameworks, vector/graph databases, Postgres/Redis, tracing/observability platforms, Azure, or ERP integrations. Specific tools are flexible; equivalent experience is welcome. Professional Qualities High ownership and follow-through. You don't wait to be told what to do next. You see what needs doing and you do it. Pragmatic and quality-conscious. You use the simplest approach that solves the problem well. You don't gold-plate, but you also don't take shortcuts that create future pain, especially when the cost of doing it right is marginal. Reliability-first mindset. You treat guardrails, evaluation, and failure handling as core engineering work, not afterthoughts. Clear communicator. You write crisp messages, document decisions, and can explain technical trade-offs plainly. Dedicated and self-driven. You're comfortable with autonomy and manage your own time effectively. You're the kind of person who, when something is running, keeps an eye on it, not because someone asked, but because you care about the outcome. Competitive compensation and benefits. The opportunity to build production AI agents used by real businesses, measured by tangible KPIs. A modern, AI-native engineering environment where you'll work with cutting-edge tooling daily. Autonomy to shape engineering standards and best practices. Career growth with executive visibility in a large, impact-oriented group. 1. Initial interview: a structured conversation to understand your experience, thinking, and motivations. 2. Paid collaborative project: instead of a contrived take-home test, you'll work on a real-scope assignment alongside other candidates over a ~2-week window, so you can fit it around your schedule. Top contributions will be awarded cash prizes. This is the core of our evaluation. We want to see how you work, not just how you talk about working. 3. Final interview: a conversation with the CEO of Aktor AI and the Head of Solution Delivery. What We Offer Hiring Process Our hiring process uses AI-assisted tools for application screening and includes an AI-powered interview stage. All decisions are made by people. Details Location: 100% Remote, in Europe or Asia Reports to: Head of Solution Delivery Collaboration: You'll work closely with the Athens-based engineering and solution delivery teams asynchronously, with regular video check-ins. Originally posted on Himalayas

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仕事探しに関するよくある質問

英語の求人が表示されるのはなぜですか?

職種名や説明文は企業が作成したものです。条件や要件を変えないように原文を掲載しています。操作画面とこのガイドは日本語です。日本語の検索で見つからない場合は、「software engineer」のように、掲載言語の職種名やスキル名でも検索してみてください。検索語が自動翻訳されるわけではありません。

リモート求人なら、どの国からでも働けますか?

必ずしもそうではありません。居住国、就労資格、勤務時間帯が指定されている場合があります。元の求人ページで条件を確認してください。記載がない場合は、自分の居住地から応募できると判断する前に企業へ確認しましょう。リモートという表示だけでは、勤務地の制限がないことは分かりません。

検索結果が出ない場合はどうすればよいですか?

より一般的な職種名や一つのスキルで検索し、条件を一つずつ外してみてください。同じような仕事でも企業によって呼び方が異なります。特定の求人が見つからなくなった場合は、企業の採用ページで求人番号を探しましょう。検索条件を広げても、終了した募集が再開するわけではありません。

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応募書類とカバーレターはどう調整すればよいですか?

募集要件と、自分が説明できるプロジェクト、業務、成果を結び付けます。経験していない技術や実績を加えず、関連する経験を分かりやすく示してください。カバーレターでは応募理由を具体例とともに伝えます。指定された言語とファイル形式に従い、送信前に両方の書類を確認しましょう。