enterprise architect

<div>Role description 
Infrastructure Solution Architect (cloud architecture,azure iaas,windows server,euc administration)

Location: London (Hybrid, 3 days onsite) 
Employment Type: Permanent / Fixed-Term 


We are seeking a visionary Infrastructure Solution Architect to lead enterprise-wide technology architecture across a broad spectrum of infrastructure domains. This is a strategic leadership role, acting as a trusted advisor to senior stakeholders and shaping the future of complex infrastructure landscapes.

You will play a pivotal role in defining and delivering scalable, secure, and innovative solutions that enable business transformation, operational resilience, and long-term growth. 


Key Responsibilities
<ul>
<li>Define and lead the end-to-end infrastructure architecture strategy, ensuring alignment with digital transformation objectives</li>
<li>Design and govern scalable, high-performance, and secure solutions across multiple domains, including:
<ul><li>Wintel &amp; Linux platforms</li>
<li>Cloud (Azure, AWS, Hybrid environments)</li>
<li>Network (LAN, WAN, SD-WAN, Wireless, Firewalls)</li>
<li>Unified Communications (Cisco, Microsoft Teams)</li>
<li>Mobility &amp; Endpoint Management (Intune, UEM/MDM)</li>
<li>Observability &amp; Monitoring (e.g., ELK, Prometheus, AppDynamics)</li>
<li>End-User Computing (VDI, Citrix, M365, OS lifecycle)</li>
<li>Service Desk &amp; End-User Services (ITSM, automation, CSAT, FCR)</li>
</ul></li><li>Act as a trusted advisor to business and IT leaders, translating strategic objectives into future-ready technical solutions</li>
<li>Lead architecture governance, ensuring compliance with enterprise standards and regulatory frameworks</li>
<li>Drive infrastructure transformation initiatives, including cloud adoption, automation, Zero Trust, SASE, and containerization</li>
<li>Evaluate emerging technologies and provide strategic recommendations</li>
<li>Collaborate with engineering, security, DevOps, and delivery teams to ensure cohesive solution design</li>
<li>Develop reference architectures, blueprints, and roadmaps</li>
<li>Support RFP/RFI responses and pre-sales engagements for large-scale programs</li>
<li>Mentor and guide architects and senior engineers, fostering a culture of technical excellence and innovation</li></ul> 


What We're Looking For
<ul>
<li>Extensive experience in IT infrastructure and architecture, with broad exposure across multiple enterprise domains</li>
<li>Strong track record designing and delivering enterprise-scale infrastructure solutions</li>
<li>Deep expertise across cloud and on-premise environments (Azure, AWS, Hybrid)</li>
<li>Strong understanding of ITSM, ITIL, and service management frameworks</li>
<li>Knowledge of security frameworks, regulatory standards, and resilience planning (e.g., ISO, NIST, DR/BCP)</li>
<li>Exceptional stakeholder management, communication, and leadership skills</li></ul> 


Preferred Certifications
<ul>
<li>TOGAF or equivalent Enterprise Architecture certification</li>
<li>ITIL (v3 / v4)</li>
<li>Microsoft, Cisco, VMware, or Red Hat certifications</li>
<li>Cloud certifications (e.g., AWS Solutions Architect, Azure Solutions Architect)</li></ul> 


Hurry &amp; apply for a more detailed conversation!

#UST 
Skills 
cloud architecture,azure iaas,windows server,euc administration,azure ad,firewall,cloud security architecure,network design,citrix xenapp,netscaler,cisco aci,network security 
About UST 
UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world&rsquo;s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients&rsquo; organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact&mdash;touching billions of lives in the process.</div>

Infrastructure Solution Architect_London (Solution Architect II - Cloud Infrastructure Services)

<div><div><div>Entity:
Technology 
Job Family Group:
IT&amp;S Group 
Job Description:
The Principal Platform Engineer is a senior individual contributor role responsible for defining the strategy and architecture for how bp's portfolio of engineering and data platforms connect, converge, and serve the organisation. This role sits at the intersection of platform engineering and enterprise architecture, providing technical leadership and strategic direction without direct line management.
The role exists to bring coherence to a distributed platform landscape, ensuring that internal engineering platforms, cloud-native infrastructure, and enterprise software-as-a-service (SaaS) solutions are integrated in a consistent, scalable, and well-governed manner. The Principal Platform Engineer is the technical authority on platform integration and convergence, influencing design decisions across teams and functions.
Key Accountabilities<ul><li>
Define and maintain a platform convergence strategy that articulates the current-state landscape, the target architecture, and a credible transition path &mdash; enabling bp's engineering platforms and SaaS solutions to operate as an integrated whole.</li><li>
Lead architectural design and decision-making at the intersection of internal platforms and enterprise SaaS, establishing integration patterns, data contracts, and governance standards that apply consistently across the platform estate.</li><li>
Act as the principal technical authority for platform engineering across the digital delivery organisation, providing expert guidance on platform design, cloud-native patterns, and systems integration to engineering teams and senior stakeholders.</li><li>
Drive resolution of complex cross-platform integration challenges, including identity, data flow, event-driven architecture, and API design &mdash; ensuring that integration decisions are durable, secure, and aligned with enterprise standards.</li><li>
Produce and maintain high-quality architecture strategy documents, reference architectures, and decision records that are accessible to both engineering and executive audiences, building shared understanding of the platform direction.</li><li>
Collaborate with AI engineering, software engineering, and external vendor and partner teams to ensure that platform architecture decisions enable and do not constrain the delivery of business and AI-powered capabilities.</li></ul>
This is a role with organisation-wide technical influence. The successful candidate will work closely with engineering managers, delivery teams, and external partners across a complex, multi-platform environment. The role requires a balance of critical thinking and hands-on technical credibility &mdash; candidates should be comfortable both authoring architecture strategy documents and engaging deeply in technical design discussions.<h1 class="jobSectionHeader">
What you will bring...</h1><ul><li>
Extensive experience in platform engineering (including Kubernetes) and the design, delivery, and operation of large-scale, multi-component platform estates in a cloud-native environment.</li><li>
Proven enterprise architecture capability, including experience producing target-state architecture strategies and navigating complex system landscapes spanning internal platforms and third-party SaaS.</li><li>
Deep knowledge of cloud-native architecture patterns: containerisation and orchestration, service mesh, API gateway design, event streaming, and infrastructure-as-code.</li><li>
Demonstrable experience integrating enterprise SaaS solutions &mdash; including ERP or business application platforms &mdash; with internally developed systems, covering API, identity, and data integration patterns.</li><li>
Track record of operating as a senior technical authority in a large organisation, influencing architecture and engineering decisions at scale without direct management responsibility.</li><li>
Strong communication and documentation skills, with the ability to convey complex architectural concepts clearly to technical peers, delivery teams, and senior business stakeholders.</li><li>
Bachelor's degree or higher in Computer Science, Software Engineering, Systems Engineering, or a related technical subject area or equivalent experience.</li><li>
Familiarity with regulatory and compliance considerations (e.g., data residency, audit logging, access control) as they apply to enterprise platform design.</li></ul>
Desirable Criteria<ul><li>
Familiarity with enterprise data platform architectures, including data mesh, data fabric, or data lakehouse patterns, and how these intersect with application and integration platforms.</li><li>
Prior experience working at the boundary of AI/ML infrastructure and broader platform engineering, including understanding of how MLOps capabilities are hosted and operated within an enterprise platform.</li><li>
Experience engaging with external software vendors and system integrators on integration architecture and platform alignment.</li><li>
Relevant professional certifications in cloud architecture or enterprise architecture (e.g., AWS Solutions Architect Professional, Azure Solutions Architect) are advantageous.</li></ul><h1 class="jobSectionHeader">
Why join us?</h1>
We&rsquo;re committed to supporting leaders who want to make an impact. At bp, you&rsquo;ll have the chance to shape and influence outcomes across businesses. You&rsquo;ll be part of an inclusive environment where diverse perspectives are valued, and where your contribution to performance and integration matters. We invest in the growth and wellbeing of our people, providing the resources, networks, and development opportunities needed to thrive.
Our total rewards package includes competitive pay, bonuses, share options, and a range of flexible benefits designed to meet your needs &mdash; from healthcare and retirement plans to paid time off and agile working. We recognise that people have multifaceted lives, and we strive to offer a career experience that reflects that.
Apply now!
Location
Please note that while this position can be based in our Sunbury office, this will move to Southwark, London by end 2027. 
Travel Requirement
Negligible travel should be expected with this role 
Relocation Assistance:
This role is not eligible for relocation 
Remote Type:
This position is a hybrid of office/remote working 
Skills:
Agility core practices, Agility core practices, API and platform design, Cloud Platforms, Collaboration, Communication, Configuration management and release, Continuous deployment and release, Creating a high performing team, Database Design, Digital Project Management, Documentation and knowledge sharing, Emerging technology monitoring, Facilitation, Information Security, Mentoring, Metrics definition and instrumentation, NoSql data modelling, Problem Solving, Relational Data Modelling, Risk Management, Scripting, Secure development, Service operations and resiliency, Software Design and Development {+ 7 more} 
Legal Disclaimer:
We are an equal opportunity employer. We do not discriminate on the basis of protected characteristics like race, religion, color, sex, national origin, sexual orientation, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp&rsquo;s recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please contact us. 
 
If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.</div>
<div>Legal Disclaimer:

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, socioeconomic status, neurodiversity/neurocognitive functioning, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp&rsquo;s recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please contact us.

If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.</div>
</div><div>Expand job description</div></div>
 <div><div>Disclaimer 


This is a high-level summary only of terms and current discretionary benefits applicable to certain roles. Some rewards, benefits and policies are at managers&rsquo; discretion and vary depending on where you work within the business. All terms subject to contract and all discretionary benefits subject to policy and eligibility.</div></div>

Principal Platform Engineer

Capgemini

<div><div><div><div>About the Job you are considering:
We are seeking an experienced Cloud &amp; Data Architecture Consultant to lead enterprise-scale cloud, data, and finance transformation initiatives. The ideal candidate will possess deep expertise in Google Cloud Platform (GCP) architecture, Oracle Integration Cloud (OIC), Enterprise Performance Management (EPM) strategy and tooling, and Databricks-based data platforms. This role will be responsible for defining target-state architectures, assessing and recommending EPM solutions, designing scalable integration frameworks, and enabling cloud-native data modernization programs. The consultant will work closely with business and technology stakeholders to drive architecture governance, solution design, and successful transformation outcomes.
Hybrid working:
The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
Your Role:
<ul><li>Define and drive enterprise-wide target-state architecture for cloud, data, and finance transformation programs.</li>
<li>Design scalable, secure, and high-performing GCP-based architecture solutions aligned with business and technology objectives.</li>
<li>Assess existing finance and performance management landscapes and provide EPM tooling recommendations based on business requirements, scalability, and future-state strategy.</li>
<li>Architect and govern Oracle Integration Cloud (OIC) solutions for seamless integration across Oracle and third-party applications.</li>
<li>Design and implement Databricks-based modern data platforms supporting analytics, reporting, and AI/ML use cases.</li>
<li>Develop enterprise data architecture standards, data models, and integration patterns to ensure consistency and scalability.</li>
<li>Lead cloud migration and modernization initiatives, including workload assessment, architecture planning, and execution oversight.</li>
<li>Collaborate with finance, business, and technology leadership teams to align architecture decisions with transformation goals.</li>
<li>Establish and enforce architecture governance, best practices, security standards, and design principles.</li>
<li>Conduct architecture reviews, solution assessments, and technical due diligence for new initiatives.</li>
<li>Provide strategic guidance on data management, integration, cloud adoption, and enterprise application modernization.</li>
<li>Facilitate stakeholder workshops, architecture discussions, and executive-level presentations.</li>
<li>Mentor project teams and support delivery organizations in implementing approved architecture solutions</li>
</ul>Your Skills:
<ul><li>Strong expertise in Google Cloud Platform (GCP) Architecture, including cloud-native design patterns and modernization strategies.</li>
<li>Hands-on experience with Oracle Integration Cloud (OIC) and enterprise integration architecture.</li>
<li>Experience evaluating, selecting, and implementing Enterprise Performance Management (EPM) solutions.</li>
<li>Strong knowledge of Databricks, data lakehouse architecture, and modern data engineering principles.</li>
<li>Expertise in Enterprise Data Architecture, data modeling, data governance, and data integration frameworks.</li>
<li>Experience in Cloud Migration, application modernization, and hybrid cloud architectures.</li>
<li>Strong understanding of solution architecture methodologies, security, scalability, and performance optimization.</li>
<li>Familiarity with data warehousing, analytics, reporting, and business intelligence ecosystems</li>
<li>Experience delivering Finance Transformation and enterprise data transformation programs.</li>
<li>Strong understanding of financial planning, forecasting, budgeting, and performance management processes.</li>
<li>Ability to translate business requirements into scalable technology solutions.</li>
<li>Excellent stakeholder management and executive communication skills.</li>
<li>Strong consulting, problem-solving, and analytical capabilities.</li>
<li>Proven experience leading architecture workshops and influencing senior business and technology stakeholders.</li>
<li>Ability to work across cross-functional and distributed teams in a fast-paced environment.</li>
<li>Strong governance, decision-making, and strategic planning skills.</li>
<li>Experience in large-scale enterprise transformation programs.</li>
<li>GCP, Oracle, Databricks, or relevant cloud certifications.</li>
<li>Experience working in consulting environments or leading enterprise architecture engagements.</li>
<li>Familiarity with finance systems, ERP platforms, and performance management ecosystems.</li>
</ul>'We are a Disability Confident Employer:
Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government&rsquo;s Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who:
<ul><li>Declare they have a disability, and</li>
<li>Meet the minimum essential criteria for the role.</li>
</ul>Please opt in during the application process.
Make It Real (what does it mean for you):
<ul><li>You&rsquo;d be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions.
 
To help support wellbeing we have trained &lsquo;Mental Health Champions&rsquo; across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.</li>
<li>You will be empowered to explore, innovate, and progress. You will benefit from Capgemini&rsquo;s &lsquo;learning for life&rsquo; mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and much more.</li>
<li>You will be joining one of the World&rsquo;s Most Ethical Companies&reg;, as recognised by Ethisphere&reg; for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of.</li>
</ul>Why you should consider Capgemini:
Growing clients&rsquo; businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you&rsquo;ll join a thriving company and become part of a collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what&rsquo;s possible. It&rsquo;s why, together, we seek out opportunities that will transform the world&rsquo;s leading businesses, and it&rsquo;s how you&rsquo;ll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you&rsquo;ll build the skills you want. You&rsquo;ll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.
About Capgemini:
Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of &euro;22.1 billion.
 
Make it real | www.capgemini.com</div></div></div></div><div></div>

Cloud & Data Architect

Google

<div><h3 class="jobSectionHeader">Minimum qualifications:</h3><ul>
<li>Bachelor's degree or equivalent practical experience.</li>
<li>6 years of experience with cloud-native architecture in technical delivery, customer engineering, or enterprise architecture and in a customer-facing or enterprise support role.</li>
<li>Experience in technical deployment planning, architecture orchestration, or technical delivery management.</li>
<li>Experience with enterprise integrations (APIs, ECMs, identity), Cloud infrastructure, and AI/ML model deployments.</li>
<li>Experience with programming languages, API integration, debugging, or enterprise systems design.</li>
<li>Experience leading technical delivery strategies, debugging systems, and interfacing with product/engineering organizations.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>L300/L400 level technical proficiency or relevant AI/ML and Cloud architecture certifications.</li>
<li>Experience guiding customers through the architectural and organizational transformations needed to deploy production-grade AI models or agents in enterprise environments.</li>
<li>Technical experience in one or more of the following: Cloud AI solutions, Enterprise Data Management, Data Analytics, Infrastructure Modernization, Security, or Cloud Networking.</li>
<li>Ability to dive deep into novel technical problems, decipher extreme ambiguity, diagnose bugs, and emerge with credible architectural solution.</li>
<li>Proven track record interfacing directly with core product and engineering organizations to escalate product bugs, advocate for feature gaps, and unblock systemic deployments.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
The Google Cloud Platform team helps customers transform and build what's next for their business &mdash; all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers &mdash; developers, small and large businesses, educational institutions and government agencies &mdash; see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As an AI Outcome Customer Engineer (AI OCE), you will drive initial and ongoing revenue ramp for our enterprise customers, clearing complex blockers and ensuring they realize maximum business value from their Cloud AI investments faster. You will manage and execute the technical deployment plan, transitioning scoped license agreements into robust production deployments by providing authoritative technical leadership to customers and partners. 
You will have a direct impact on the velocity and incremental consumption of customer agreements, leading to accelerated value realization, higher adoption, and future expansion opportunities. You will blend sales acumen, enterprise architecture knowledge, technical engagement, and technical delivery management to prove and scale the value of Google's premier Cloud AI solutions.
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Develop and orchestrate a structured, end-to-end technical deployment plan across customer and partner teams. Lead upfront architectural validation to ensure integration readiness before execution begins.</li>
<li>Dive into complex technical workflows to diagnose, debug, and resolve implementation roadblocks. Act as a technical bridge to core product and support engineering teams to eliminate systemic friction and accelerate customer delivery.</li>
<li>Drive and track the progress of the initial and ongoing ramp of Cloud AI license agreements, guiding enterprise workloads from agreement to active consumption as rapidly and securely as possible.</li>
<li>Partner collaboratively with Account an CEs team during the technical evaluation phase of key deals to ensure proposed Cloud AI solutions are architected for viable, scalable long-term adoption.</li>
<li>Drive sustainable, secure Cloud AI product usage to help customers continuously realize quantifiable business outcomes and secure future contract renewals.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

AI Outcome Customer Engineer, Cloud AI Tech GTM

Accenture

<div>YOU ARE
As a hands-on AI/LLM Architect, you will be at the heart of designing and building advanced AI systems that power the modern enterprise. This is a deeply technical, hands-on &mdash; you will spend the majority of your time in the architecture and engineering of real-world AI solutions across classical machine learning, generative AI, and agentic systems, delivering these within active client engagements. You will translate requirements into concrete architecture decisions: selecting design patterns, evaluating and benchmarking technical frameworks, assembling reusable components, and making deliberate technology choices that balance innovation with enterprise-grade reliability. You will design and build AI agent architectures &mdash; including multi-agent orchestration, tool use, skills use, and memory systems &mdash; and work hands-on with foundation models through fine-tuning, retrieval-augmented generation (RAG), and custom model integration. A part of your work will also involve engineering the AI context layer that makes these systems intelligent in practice &mdash; connecting enterprise knowledge bases, structured and unstructured data sources, and domain-specific content so that AI outputs are grounded, accurate, and relevant to the client's business. You will design and validate systems against enterprise non-functional requirements across security, observability, governance, performance, and scalability. A core output of this is the production of tangible engineering and architecture deliverables. This means writing and owning software components &mdash; building, integrating, and testing AI system modules as a practitioner &mdash; alongside producing detailed architecture artifacts including architecture decision records (ADRs), component diagrams, data flow diagrams, and integration specifications that guide and enable broader engineering teams. You will work with cross-functional delivery teams alongside data engineers, ML engineers, and application developers, and this is an opportunity to develop deep expertise across the full AI architecture stack, sharpen your engineering instincts on complex, real-world problems, and build a foundation for growing into a lead or principal architect over time.
THE WORK<ul><li>
Independently design, build, and deliver software components across the AI architecture &mdash; owning them end to end from design through implementation, integration, and testing as a hands-on practitioner</li><li>
Design and build AI agent architectures &mdash; including individual agents, their prompts, tools, and skills, multi-agent orchestration, and memory systems &mdash; making deliberate design pattern and technology choices</li><li>
Design and implement agent orchestration patterns that handle task handoffs, communication, state management, and error recovery, validating them through hands-on prototyping</li><li>
Evaluate multiple design options and technical approaches, making deliberate, justified design choices that balance capability, cost efficiency, performance, and enterprise-grade reliability</li><li>
Design, build, and run evaluation strategies and harnesses that measure agent and system quality on metrics such as accuracy, relevance, and faithfulness, translating findings into design improvements</li><li>
Architect and implement foundation model integrations &mdash; selecting the right models, invocation patterns, and customization approaches (fine-tuning, RAG, custom integration) based on capability, cost, and performance trade-offs</li><li>
Design and build model adaptation and fine-tuning pipelines, applying working knowledge of transformer-based architectures to inform model selection and optimization</li><li>
Design and build the AI context layer &mdash; including context graph design and ingestion pipelines that parse, chunk, enrich, and index structured and unstructured enterprise content, and the retrieval components that ground AI outputs in the client's knowledge</li><li>
Build embedding, vector storage, and retrieval (semantic, hybrid, reranking) into end-to-end RAG pipelines, applying integration patterns that connect to enterprise data sources</li><li>
Design and implement context assembly and memory components that manage prompts, context windows, and conversational state for grounded, accurate outputs</li><li>
Identify, design, and build reusable components and solution patterns that accelerate delivery and can be templated across engagements</li><li>
Design for cost efficiency and performance &mdash; optimizing model usage, inference patterns, caching, and resource utilization to meet target latency, throughput, and cost objectives</li><li>
Design, build, and validate systems against enterprise non-functional requirements &mdash; implementing guardrails, prompt-injection defenses, PII handling, and access controls for security and Responsible AI</li><li>
Build governance controls including versioning, audit logging, and lineage tracking, and produce the model documentation that keeps systems auditable</li><li>
Build observability into systems &mdash; logging, tracing, monitoring, alerting, and cost tracking &mdash; to ensure AI solutions remain healthy, performant, and scalable in production</li><li>
Produce detailed architecture artifacts &mdash; including architecture decision records (ADRs), architecture blueprints, design documents, agent orchestration and integration pattern specifications, component and data flow diagrams &mdash; that guide and enable broader engineering teams</li><li>
Continuously learn, evaluate, and apply new design patterns, frameworks, and technologies across the fast-evolving AI landscape, balancing innovation with enterprise-grade reliability</li><li>
Collaborate with cross-functional delivery teams &mdash; data engineers, ML engineers, and application developers &mdash; to translate requirements into concrete architecture decisions that meet stakeholder needs</li></ul></div>
 
<div>EDUCATION<ul><li><ul><li>Bachelor's Degree or equivalent</li></ul></li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Experience in designing &amp; deploying AI / ML solutions using at least one cloud vendor as an AI/ML architect.</li><li>
Recent experience in the Agentic, LLM and Generative AI space.</li><li>
Experience architecting and operationalizing LLM driven application architecture patterns.</li><li>
Experience coding and engineering, machine learning, deep learning and NLP solutions and applications. Coding experience using python</li></ul></div>

AI LLM Technology Architecture Specialist

<div>YOU ARE
As a hands-on AI/LLM Architect, you will be at the heart of designing and building advanced AI systems that power the modern enterprise. This is a deeply technical, hands-on &mdash; you will spend the majority of your time in the architecture and engineering of real-world AI solutions across classical machine learning, generative AI, and agentic systems, delivering these within active client engagements.
You will translate requirements into concrete architecture decisions: selecting design patterns, evaluating and benchmarking technical frameworks, assembling reusable components, and making deliberate technology choices that balance innovation with enterprise-grade reliability. You will design and build AI agent architectures &mdash; including multi-agent orchestration, tool use, skills use, and memory systems &mdash; and work hands-on with foundation models through fine-tuning, retrieval-augmented generation (RAG), and custom model integration.
A part of your work will also involve engineering the AI context layer that makes these systems intelligent in practice &mdash; connecting enterprise knowledge bases, structured and unstructured data sources, and domain-specific content so that AI outputs are grounded, accurate, and relevant to the client's business.
You will design and validate systems against enterprise non-functional requirements across security, observability, governance, performance, and scalability.
A core output of this is the production of tangible engineering and architecture deliverables. This means writing and owning software components &mdash; building, integrating, and testing AI system modules as a practitioner &mdash; alongside producing detailed architecture artifacts including architecture decision records (ADRs), component diagrams, data flow diagrams, and integration specifications that guide and enable broader engineering teams.
You will work with cross-functional delivery teams alongside data engineers, ML engineers, and application developers, and this is an opportunity to develop deep expertise across the full AI architecture stack, sharpen your engineering instincts on complex, real-world problems, and build a foundation for growing into a lead or principal architect over time.
THE WORK<ul><li>
Independently design, build, and deliver software components across the AI architecture &mdash; owning them end to end from design through implementation, integration, and testing as a hands-on practitioner</li><li>
Design and build AI agent architectures &mdash; including individual agents, their prompts, tools, and skills, multi-agent orchestration, and memory systems &mdash; making deliberate design pattern and technology choices</li><li>
Design and implement agent orchestration patterns that handle task handoffs, communication, state management, and error recovery, validating them through hands-on prototyping</li><li>
Evaluate multiple design options and technical approaches, making deliberate, justified design choices that balance capability, cost efficiency, performance, and enterprise-grade reliability</li><li>
Design, build, and run evaluation strategies and harnesses that measure agent and system quality on metrics such as accuracy, relevance, and faithfulness, translating findings into design improvements</li><li>
Architect and implement foundation model integrations &mdash; selecting the right models, invocation patterns, and customization approaches (fine-tuning, RAG, custom integration) based on capability, cost, and performance trade-offs</li><li>
Design and build model adaptation and fine-tuning pipelines, applying working knowledge of transformer-based architectures to inform model selection and optimization</li><li>
Design and build the AI context layer &mdash; including context graph design and ingestion pipelines that parse, chunk, enrich, and index structured and unstructured enterprise content, and the retrieval components that ground AI outputs in the client's knowledge</li><li>
Build embedding, vector storage, and retrieval (semantic, hybrid, reranking) into end-to-end RAG pipelines, applying integration patterns that connect to enterprise data sources</li><li>
Design and implement context assembly and memory components that manage prompts, context windows, and conversational state for grounded, accurate outputs</li><li>
Identify, design, and build reusable components and solution patterns that accelerate delivery and can be templated across engagements</li><li>
Design for cost efficiency and performance &mdash; optimizing model usage, inference patterns, caching, and resource utilization to meet target latency, throughput, and cost objectives</li><li>
Design, build, and validate systems against enterprise non-functional requirements &mdash; implementing guardrails, prompt-injection defenses, PII handling, and access controls for security and Responsible AI</li><li>
Build governance controls including versioning, audit logging, and lineage tracking, and produce the model documentation that keeps systems auditable</li><li>
Build observability into systems &mdash; logging, tracing, monitoring, alerting, and cost tracking &mdash; to ensure AI solutions remain healthy, performant, and scalable in production</li><li>
Produce detailed architecture artifacts &mdash; including architecture decision records (ADRs), architecture blueprints, design documents, agent orchestration and integration pattern specifications, component and data flow diagrams &mdash; that guide and enable broader engineering teams</li><li>
Continuously learn, evaluate, and apply new design patterns, frameworks, and technologies across the fast-evolving AI landscape, balancing innovation with enterprise-grade reliability</li><li>
Collaborate with cross-functional delivery teams &mdash; data engineers, ML engineers, and application developers &mdash; to translate requirements into concrete architecture decisions that meet stakeholder needs</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree or equivalent</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Experience in designing &amp; deploying AI / ML solutions using at least one cloud vendor as an AI/ML architect.</li><li>
Experience in the Agentic, LLM and Generative AI space.</li><li>
Experience architecting and operationalizing LLM driven application architecture patterns.</li><li>
Expertise in coding with Python and engineering, machine learning, deep learning and NLP solutions and applications.</li></ul></div>

AI LLM Technology Architecture Assoc Manager

Mastercard

<div>Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we&rsquo;re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Senior Principal Agentic Platforms Architect
Overview
 
 
The AI Center of Excellence is seeking a Senior Principal Agentic Platforms Architect to lead the technical vision, architecture, and hands-on development of Mastercard's enterprise agentic AI platforms. This role demands deep, demonstrated expertise in building and shipping production-grade AI and agentic systems at enterprise scale, combined with the architectural rigor required to operate within one of the most highly regulated and security-conscious environments in the world. Reporting to senior leadership, you will own the E2E platform architecture for agentic AI systems, from runtime orchestration and governance infrastructure through to production deployment and operational lifecycle management. This is not a strategy-only role. You will write code, review code, and hold the team to the highest standards of engineering excellence. The right candidate has spent their career building AI systems that run in production, not prototypes, not proofs of concept, but systems that operate at scale, under load, and under scrutiny 
 
Role
 
 
<ul><li>Serve as the principal technical authority for agentic AI platform architecture, owning the design and evolution of runtime environments, governance layers, orchestration engines, and multi-tenancy infrastructure that support enterprise-grade AI agent deployment</li></ul> 
<ul><li>Lead hands-on architecture and development of agentic systems, including agent orchestration frameworks, tool and model integration layers, policy enforcement engines, guardrail systems, behavioral monitoring pipelines, and evaluation infrastructure</li></ul> 
<ul><li>Design and implement scalable, resilient platform architectures that support multi-agent coordination, A2A communication protocols, memory governance, and real-time observability across distributed deployments</li></ul> 
<ul><li>Drive the technical strategy for model integration and abstraction, enabling model-agnostic agent execution across multiple providers while enforcing cost optimization, routing intelligence, and governance controls at the platform level</li></ul> 
<ul><li>Architect and build API-first platform interfaces that enable both internal teams and external consumers to build, deploy, govern, and operate AI agents through programmatic, language-agnostic access patterns</li></ul> 
<ul><li>Define and enforce engineering standards, code quality practices, and architectural governance across the platform engineering team, ensuring every component meets production-grade requirements for security, resilience, performance, and compliance</li></ul> 
<ul><li>Provide deep technical leadership on agentic AI design patterns, including retrieval-augmented generation, tool calling via Model Context Protocol, multi-step orchestration, human-in-loop workflows, and autonomous decision-making architectures</li></ul> 
<ul><li>Act as a trusted technical advisor to senior leadership, translating complex platform architecture decisions into clear, business-oriented language that supports informed decision-making at the executive level</li></ul> 
<ul><li>Mentor and develop a high-performing engineering team, fostering a culture of technical excellence, intellectual honesty, rigorous code review, and continuous improvement</li></ul> 
<ul><li>Produce and maintain authoritative architectural documentation, including system design documents, architecture decision records, and integration specifications that meet Mastercard's engineering principles and security standards</li></ul> 
All About You
 
 
<ul><li>15+ years of hands-on experience in software engineering and AI engineering, with a significant and demonstrable portion spent designing, building, and shipping AI and machine learning systems to production at enterprise scale</li></ul> 
<ul><li>Proven track record of architecting and delivering agentic AI systems, autonomous agents, multi-agent orchestration platforms, or AI-powered automation systems that operate in production with real users, real data, and real consequences</li></ul> 
<ul><li>Deep hands-on coding proficiency. You write production code, you review production code, and you hold others to the same standard. This is a building role, not a diagram-drawing role</li></ul> 
<ul><li>Advanced expertise in Python and modern AI/ML frameworks, with hands-on experience across agentic toolkits such as LangChain, LangGraph, CrewAI, or equivalent orchestration frameworks</li></ul> 
<ul><li>Strong architectural experience with cloud-native platforms including AWS, Databricks, and Kubernetes, with demonstrated ability to design for high availability, fault tolerance, and horizontal scalability</li></ul> 
<ul><li>Deep understanding of AI governance, trust, and safety architectures, including guardrail systems, policy engines, behavioral analytics, evaluation frameworks, red teaming methodologies, and compliance mapping</li></ul> 
<ul><li>Experience designing and building multi-tenant platforms with fine-grained access control, workspace isolation, and enterprise-grade identity and authorization systems</li></ul> 
<ul><li>Proven ability to design API-first architectures, RESTful interfaces, and SDK abstractions that serve both internal platform teams and external consumers</li></ul> 
<ul><li>Strong understanding of data architectures including Delta Lake, data lakehouse patterns, vector databases and retrieval-augmented generation pipelines</li></ul> 
<ul><li>Demonstrated experience with tool calling architectures and model-agnostic integration patterns across multiple LLM providers</li></ul> 
<ul><li>Exceptional communicator who can articulate deeply technical architecture decisions to engineering teams and translate complex platform concepts into business language for non-technical stakeholders</li></ul> 
<ul><li>Known for building trust, holding high standards, and mentoring engineers. You make the people around you better. Motivated by hard problems, not titles. You bring intellectual curiosity, resilience, and relentless energy to complex technical challenges</li></ul> 
<ul><li>Bachelor's degree in Computer Science, Engineering, or a related field. Advanced degree preferred but not required if the experience speaks for itself</li></ul>
Corporate Security Responsibility 
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:<ul><li>
Abide by Mastercard&rsquo;s security policies and practices;</li><li>
Ensure the confidentiality and integrity of the information being accessed;</li><li>
Report any suspected information security violation or breach, and</li><li>
Complete all periodic mandatory security trainings in accordance with Mastercard&rsquo;s guidelines.</li></ul></div>

Senior Principal Agentic Platforms Architect

Explore 105+ Enterprise architect in London this July. Find roles across top companies and apply now to boost your career.