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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Ops Platform Architect - **Company:** Mphasis - **Location:** London, UK - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Information Engineering, Software Design Patterns, Machine Learning, Software Deployment, Software Engineering, Google Cloud, Large Language Models, Multi-Agent Systems, IT Architecture, Generative AI, Data Management, Machine Learning Operations, Virtual Agents - **Published:** July 10, 2026 - **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=2865358217-2 ## About the Role We are seeking an experienced and highly skilled AI Architect to provide strategic leadership and hands-on expertise in designing, implementing, and scaling enterprise AI solutions. This role requires a proven specialist capable of translating business objectives into AI-driven outcomes while ensuring alignment with enterprise architecture, governance, and operational requirements., * Extensive experience in enterprise architecture, AI/ML solution design, and digital transformation programs. * Strong knowledge of cloud platforms such as Microsoft Azure, Amazon Web Services AWS, and Google Google Cloud. * Experience with Generative AI frameworks, AI orchestration platforms, and MLOps practices. * Proven track record of delivering AI solutions from concept through production at enterprise scale. * Understanding of Responsible AI, AI governance, model lifecycle management, and AI risk frameworks. * Excellent problem-solving, analytical, and strategic thinking capabilities. ## Description * Help identify and evaluate evolving AI/Agentic/Automation technologies, tools, and approaches that could benefit CLIENT and apply in their context (Controls/Governance/Domain) * Help drive Program functions described above to exploit full value of AIOps related spends and efforts * Work with underlying CLIENT platform teams to review and evaluate their Roadmaps for enablers/dependencies within the overall AIOps Business Case * Help continuously evolve and enhance the AIOps Business Case * Provide expert architectural leadership for AI and Generative AI initiatives, leveraging extensive experience in enterprise-scale technology transformation and AI adoption programs. * Design end-to-end AI solution architectures, including machine learning, Generative AI, agentic AI, data platforms, and cloud-based AI services. * Work closely with business stakeholders, product owners, technology teams, and program leadership to identify and prioritize AI use cases that deliver measurable business value. * Define and implement AI architecture standards, design patterns, governance frameworks, and best practices across the organization. * Possess deep expertise in AI/ML technologies, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, vector databases, and modern AI platforms. * Lead the evaluation, selection, and integration of AI tools, platforms, and services while ensuring scalability, security, reliability, and cost optimization. * Translate business requirements into technical solution designs and provide guidance throughout the development and deployment lifecycle. * Ensure compliance with enterprise security, privacy, responsible AI, and regulatory requirements. * Act as a hands-on contributor, supporting solution teams in architecture reviews, proof-of-concepts, pilot implementations, and production deployments. * Collaborate with data engineering, application development, and infrastructure teams to establish robust AI operating models and delivery frameworks. * Identify and mitigate technical, operational, and governance risks associated with AI implementations. * Develop AI roadmaps and reference architectures that support long-term organizational strategy and innovation objectives. * Demonstrate exceptional communication and stakeholder management skills, particularly when engaging with senior leadership and executive stakeholders. * Operate effectively in fast-paced, dynamic environments, delivering measurable outcomes and accelerating AI adoption across the enterprise. ## Related Videos - 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