AI Conversational Platform Manager/Engineer – ICT AI Engineer

ppAt Sixsentix, we don’t just test software—we accelerate innovation. As a leading provider of quality assurance software testing services, we empower global enterprises to deliver high-quality solutions continuously faster and smarter. Our secret? A fearless blend of cutting‑edge tools, proven methodologies and an approach that thrives on bold ideas. /p pAcross all industries, we are the driving force behind some of the most successful digital transformations and platform innovation in Europe and beyond. /p h3Why Join Us? /h3 ul liImpact from Day One: Your work will directly shape the digitalization of leading companies /li liExpert Collaboration: Work alongside some of the brightest minds in quality assurance and testing /li liGlobal Reach, Local Support: Be part of a diverse, international team with consultants in Switzerland, Serbia, Austria, Germany, Poland and the UAE /li liContinuous Learning: We champion growth-through training, mentorship and a culture that celebrates curiosity /li liInclusive Culture: We value diversity and believe that different perspectives make us stronger /li /ul h3Who We’re Looking For /h3 pWe are looking for an AI Conversational Platform Manager (hereafter referred to as Companion Manager) with 3–7 years of professional experience in business analysis, requirements engineering, knowledge management, QA, consulting, or a related field. /p pYou combine strong business understanding with a structured, quality-focused mindset and hands‑on experience applying AI tools in a professional environment. You understand that reliable enterprise AI requires more than good prompts: it requires high‑quality knowledge, clear instructions, systematic evaluation, controlled change, and strong governance. /p pThe role sits close to Solutioning and client delivery. You will work with client and internal experts from early solution development through funded pilots, PoCs, pilots, and readiness for broader use. Depending on the engagement, this includes direct client interaction, workshops, and on‑site collaboration. /p pThis is not about building a generic chatbot. It is about creating reliable, repeatable, measurable, and trusted AI Companion behavior for enterprise environments — and turning what works into reusable delivery assets that can scale across clients through the Gate. /p pThe title Manager refers to ownership of Companion quality, knowledge, and lifecycle rather than line management. /p h3What we offer /h3 ul liThe opportunity to work at the intersection of AI, business, quality engineering and knowledge management /li liA key role in shaping how enterprise AI Companions support consulting and delivery, including Companion knowledge, AI Skills, prompts and quality standards /li liEngaging projects across various sectors, including banking, insurance, manufacturing, retail, electronics and more /li liAn environment where you can leverage your previous experience while applying new ways of working through AI-enabled and innovative approaches, including our Agent Business Model /li liClose collaboration with Business Analysts, AI Architects, testers, delivery teams and a community of experienced professionals in Quality Assurance and IT /li liThe opportunity to contribute to scalable, AI-enabled delivery approaches in complex enterprise environments /li liFlexible working hours with the option to work from home /li liTeam events designed to help you connect, exchange knowledge and grow together with your colleagues /li liAttractive fringe benefits, such as extra holidays, sports support, tenure awards and more /li /ul h3Your responsibilities /h3 ul liOwn and maintain Companion knowledge, prompts, instructions, AI Skills, and configurations through a controlled and versioned lifecycle /li liTranslate business, process, requirements, and QA documentation into structured, Companion‑ready knowledge /li liFacilitate sessions with client and internal subject‑matter experts to capture domain knowledge, terminology, requirements, and expected behavior /li liDefine and apply quality criteria, test sets, sampling, regression checks, and evaluation approaches to measure Companion performance and identify improvement needs /li liReview Companion outputs for correctness, grounding, terminology consistency, business usefulness, and risk /li liEstablish the risk‑based testing foundation and support/run testing analysis where required by the delivery methodology /li liMaintain traceability between business knowledge, requirements, Companion configuration, AI Skills, test evidence, and outputs /li liEnsure confidential and sensitive client information is handled in line with enterprise data, security, and governance requirements /li liOwn data quality for Companion knowledge sources, identify duplication, inconsistency, and stale content; define cleansing and deduplication routines /li liDefine and maintain data governance rules for Companion knowledge (ownership, update cadence, source‑of‑truth mapping across tools) /li liCoordinate integration of Companion knowledge and configuration via MCP/API connections to source systems, ensuring data flowing into Companions is accurate, current, and correctly scoped /li liCollaborate with ABM Solution Architects, AI Agent developers, testers, delivery teams, and client stakeholders to align Companion behavior with business and QA objectives /li liSupport Companion adoption from pilot through readiness, including onboarding, usage guidance, feedback loops, and integration into day‑to‑day delivery /li liPackage validated knowledge, skills, evaluation assets, and proven patterns so they can be reused and compounded across clients /li /ul h3Your profile /h3 ul li3–7 years of relevant professional experience in business analysis, requirements engineering, knowledge management, QA, consulting, or a related role /li liStrong understanding of business processes and the ability to structure complex domain knowledge clearly /li liExperience working with requirements, user stories, process documentation, test assets, or comparable delivery artefacts /li liHands‑on experience using an LLM assistant, AI platform, or agent‑based solution in a professional context /li liDemonstrated ability to evaluate AI‑generated outputs for correctness, grounding, consistency, relevance, and risk /li liExperience with structured quality evaluation, testing, or measurement approaches /li liStrong written communication skills, with the ability to create clear knowledge content, instructions, guidance, and AI‑ready documentation /li liExperience eliciting requirements and domain knowledge from business stakeholders and subject‑matter experts /li liExperience with data governance, data quality management, or master data concepts /li liFamiliarity with system integration approaches (API, MCP) for connecting knowledge/data sources to AI platforms /li liAbility to work responsibly with confidential client documentation and enterprise data‑protection requirements /li liConfidence working in client‑facing environments, including workshops and on‑site collaboration where required /li liExperience in enterprise QA, test management, SDLC, or risk‑based testing is an advantage /li liExperience working with version‑controlled artefacts, peer review, and structured release processes is an advantage /li liHands‑on experience with AI Companion or agent platforms, such as Microsoft Copilot, Copilot Studio, or comparable solutions, is an advantage. /li liFamiliarity with RAG‑based systems, prompt management, AI‑assisted knowledge retrieval, and AI agent concepts is beneficial /li liISTQB certification is considered an advantage /li liExperience in regulated or complex industries such as banking, insurance, telecom, healthcare, or the public sector is an advantage /li liFluency in German and English is required /li /ul /p #J-18808-Ljbffr