AI Architect
Hitachi Solutions
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Preparing for this interview
Interviews for architect roles keep coming back to AWS, Python, Azure, GCP. Practise those questions before you sit with Hitachi Solutions.
Questions you are likely to be asked
- Why do you want to join Hitachi Solutions?
- What is your experience with Generative AI? Tell me one thing you learned the hard way.
- How would you explain your model's result to someone who is not technical?
- What would you check first if a model's accuracy dropped after going live?
- When would you not use machine learning for a problem?
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Practise the AI Architect at Hitachi Solutions interview free →We are growing our consulting team, and looking for an experienced AI Architect to lead the design and delivery of secure, scalable and responsible AI solutions across enterprise and public‑sector programmes. This role combines hands‑on technical expertise with strong architectural leadership, shaping end‑to‑end AI solutions from early discovery through to production delivery and scale. You will act as a trusted advisor to clients and internal teams, defining AI architectures, setting standards and guardrails, and ensuring AI is applied where it delivers real business value. Key Responsibilities Design and own end‑to‑end AI client-specific solution architectures, including Generative AI, Agents and traditional ML. Define and maintain enterprise AI architecture patterns, reference architectures, and reusable building blocks within the Microsoft ecosystem. Lead AI governance, security and Responsible AI by design, ensuring solutions meet regulatory, ethical and organisational standards. Provide architectural oversight across delivery teams, ensuring quality and scalability. Support pre‑sales and discovery, shaping solution approaches and technical estimates and delivery roadmaps. Advise stakeholders on AI feasibility, trade‑offs, risks and long‑term sustainability. Build hands-on prototypes, reference implementations and reusable accelerators to remain close enough to the code to set credible technical direction and unblock delivery teams. Required Skills & Experience Significant overall experience delivering AI and Data solutions in complex enterprise environments, with a minimum of 5 years hands-on AI delivery experience. Proven experience delivering production-grade AI solutions end‑to‑end, from discovery through to live operations and ongoing model management. Hands-on expertise across Microsoft cloud and AI ecosystem, including Microsoft Foundry and data platform. Strong experience with integrating low-code Power Platform solutions into enterprise-scale solutions, including hands-on experience with Copilot Studio. Solid understanding of Microsoft security, identity and compliance (Entra ID, RBAC, network isolation, data protection). Strong experience designing LLM‑based solutions, including Retrieval‑Augmented Generation (RAG), prompt engineering strategies and agent‑based architectures, leveraging frameworks such as Semantic Kernel, LangChain, and Microsoft Agent Framework. Deep practical experience with classical Machine Learning, including supervised and unsupervised learning, feature engineering, model selection, training pipelines, evaluation frameworks and production lifecycle management, equivalent in depth to GenAI expertise. Proven ability to assess client use cases and make well-reasoned architectural decisions between classical ML and Generative AI approaches; and articulate clearly why. Strong experience in cloud‑native architecture, including API‑based and event‑driven designs, enterprise integration patterns and architectures focused on scalability, resilience and reliability. Experience with DevOps, MLOps and LLMOps practices, including CI/CD pipelines, automated testing, environment strategies and operating LLM‑based solutions in production, with a strong focus on model and prompt lifecycle management, observability and evaluation, reliability and cost management. Strong understanding of Generative AI governance, operational controls and cost evaluation, including monitoring usage, performance and designing solutions that are supportable, auditable and sustainable at scale. Strong experience embedding Responsible AI and governance into Generative AI solutions, covering safety, risk management, transparency, explainability, human‑in‑the‑loop design and regulatory alignment. Desirable experience in integrating enterprise data platforms with AI solutions, including familiarity with Lakehouse architectures and data engineering principles. Proven experience in a consulting role, with the ability to translate complex technical concepts into clear business outcomes, effectively engaging non‑technical stakeholders and senior leaders. Good experience of managing and mentoring junior AI engineers or consultants. Must hold at least two relevant Microsoft certifications (AI-901, AI-103, DP-800 AZ‑305., AI-300),or be actively working towards them. Candidates must hold, or be eligible for, UK Security Clearance. In applying for a role with Hitachi Solutions Europe Limited and/or its affiliates (“Hitachi”) you consent to Hitachi collecting and storing your personal information (including your name, job title and email address) in relation to this role and any others that may be suitable in the future. For more information please refer to our Privacy Policy located at Privacy policy (hitachi-solutions.co.uk) Beware of scams Our recruiting team may communicate with candidates via our @hitachisolutions.com domain email address and/or via our SmartRecruiters (Applicant Tracking System) notification@smartrecruiters.com domain email address regarding your application and interview requests. All offers will originate from our @hitachisolutions.com domain email address. If you receive an offer or information from someone purporting to be an employee of Hitachi Solutions from any other domain, it may not be legitimate.
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Listed on smartrecruiters · posted 2026-07-17. ApplySarthi collects openings and links to application pages; the role is advertised by Hitachi Solutions, not by us.