solution 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)

Google

<div>Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Frankfurt, Germany; Munich, Germany; London, UK.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience.</li>
<li>7 years of experience designing and deploying cloud-based solutions.</li>
<li>5 years of experience in financial services, specifically capital markets or digital assets.</li>
<li>Experience of Web3 technology, including blockchain and DLT.</li>
<li>Experience advising executive stakeholders on technical strategy and integration.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Master's degree in Computer Science, Engineering, or a related technical field.</li>
<li>Experience selling Web3 solutions to TradFi companies managing stakeholder concerns and identifying where DLT provides the most commercial value.</li>
<li>Expertise in advanced Web3 concepts, including smart contracts (e.g., solidity), zero-knowledge proofs, and consensus mechanisms, including their associated security challenges.</li>
<li>Knowledge of the exchange business, including high-frequency trading and how decentralized technology integrates with existing financial business models.</li>
<li>Understanding of European digital asset regulations and sovereign initiatives, such as the digital Euro.</li>
<li>Excellent communication and influence skills, with an ability to manage complex stakeholder expectations in high-pressure environments.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
This role sits within the Global Solutions and Consumer AI organization within Google Cloud. Their role is accelerate customer value and increase adoption by delivering innovative, repeatable, and enterprise-ready solutions focused on business value. Make Google Cloud the preferred choice for customers by delivering the highest-value, industry relevant solutions.
As a Solution Architect, Web3 and Digital Assets, you will bridge the gap between traditional financial market infrastructure and the frontier of digital assets. You will act as the primary technical advisor for driving Web3 and blockchain initiatives. In this role, you will help the world&rsquo;s leading exchange organizations navigate the shift toward decentralized technology while maintaining the stability and security required by capital markets.
You will operate with near initiative, challenging traditional assumptions and advocating for an innovation agenda that balances technical possibility with commercial reality. You will push partnerships forward, ensuring that both Google Cloud and our customers achieve significant progress in co-innovating for the future of finance.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
 
 
Germany: &euro;148000 - &euro;152000 (EUR) + 20% bonus target + equity + benefits 
 
Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Push the envelope by proposing innovative solutions that challenge traditional assumptions, advising executive leaders on where Web3 and DLT can be reasonably introduced into financial processes to bring genuine business value.</li>
<li>Translate unclear requirements into concrete technical blueprints, architecting end-to-end solutions for digital asset trading, clearing, and settlement using Google Cloud technology.</li>
<li>Align diverging views across different business units and funnel new initiatives through commercial frameworks ensuring stakeholder alignment despite political complexities or organizational inertia.</li>
<li>Oversee the end-to-end execution of Web3-related projects, defining milestones and SOWs for partner-led delivery while rigorously monitoring progress to ensure technical solutions meet Google&rsquo;s high standards for stability and security.</li>
<li>Represent Google Cloud&rsquo;s view on the Web3 space to the industry, generating visibility through blog posts and speaking engagements to showcase the co-innovation occurring between Google Cloud and our customers.</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>

Solutions Architect, Web3 and Digital Asset, Google Cloud

New Look

We’re the feel-good fashion brand making style accessible and fun for over 55 years, on our website, mobile app and over 300 stores in the UK.
 
By living our values - we play to win, customer obsessed, we are one and it starts with me - we deliver That New Look Feeling for our customers and each other.
 
THE ROLE: 
As Domain Architect for Integration at New Look, you will be responsible for shaping and leading the architecture direction for enterprise integration across the technology estate.
 
You will define and maintain the integration strategy, target architecture, standards, patterns and roadmap for how systems, services, platforms and suppliers connect across the organisation.
 
You will work across business portfolios, product teams, engineering, security, infrastructure, data, suppliers and delivery partners to ensure that integration decisions are secure, resilient, scalable, maintainable and aligned to enterprise architecture strategy.
 
You will provide specialist architecture leadership to Solution Architects and engineering teams, ensuring that integration designs are coherent, reusable and appropriate to business and operational needs
 
WHAT YOU’LL BE DOING: 
Integration Architecture
 <ul>
<li>Integration Strategy: Define, implement and maintain the enterprise integration architecture strategy, target state and roadmap. Ensure that integration decisions align with New Look’s business strategy, technology strategy and enterprise architecture principles.</li>
<li>Integration Standards: Define and maintain standards, principles, patterns and guardrails for APIs, events, messaging, batch, file exchange, orchestration and service interaction. Ensure standards are practical, reusable and understood by architects and delivery teams.</li>
<li>Architecture Coherence: Ensure integration designs are coherent across applications, platforms, data, security, infrastructure, operations and supplier solutions. Challenge point-to-point, duplicated or short-term integration approaches where they increase risk or complexity.</li>
<li>Technology Simplification: Identify integration technology debt, platform risks and capability gaps. Define pragmatic remediation and modernisation approaches that support business agility, resilience, cost control and long-term maintainability.</li>
</ul>
Platform and Technology Direction
 <ul>
<li>Platform Architecture: Provide architecture leadership for enterprise integration platforms, API management, messaging and eventing capabilities. Ensure platforms are scalable, secure, resilient, observable and fit for current and future needs.</li>
<li>Roadmap Planning: Support platform roadmap planning, lifecycle management and investment decisions for integration capabilities. Ensure roadmap choices are informed by business priorities, platform health, technology debt, supplier risk and operational impact.</li>
</ul>
Architecture Guidance and Assurance
 <ul>
<li>Collaborate with Stakeholders: Work closely with Group Architects, Solution Architects, engineering teams, business stakeholders and external vendors to understand integration needs and translate them into appropriate architecture guidance. Engage with senior technology and delivery stakeholders to ensure integration decisions meet business and IT requirements at a strategic level.</li>
<li>Solution Support: Advise projects, products and programmes on integration options, service boundaries, non-functional requirements, dependencies and risks. Support solution options, high-level designs, architecture decision records and key design decisions where integration complexity or reuse potential is significant.</li>
<li>Architecture Governance: Provide integration architecture authority into architecture review and Design Authority activity. Ensure material integration decisions are evidence-based, traceable and aligned to enterprise standards.</li>
</ul>
Leadership and Community
 <ul>
<li>Technical Leadership: Lead, manage or mentor Solution Architects and aligned technical architecture roles where required. Provide guidance to engineering and delivery teams on the appropriate use of integration standards and patterns.</li>
<li>Architecture Community: Contribute to the ongoing improvement of New Look’s architecture framework, integration artefacts, governance process and architecture community.</li>
<li>Knowledge Sharing: Promote integration best practice across architects, engineers, product teams and suppliers. Ensure learning from delivery is fed back into standards, patterns and roadmaps.</li>
<li>Responsible Use of AI Tools: Use approved AI tools to support research, pattern analysis, documentation, design review and architecture decision preparation. Ensure AI-generated outputs are validated before use in decisions, standards or stakeholder communication.</li>
<li>AI-Enabled Integration: Assess the integration implications of AI systems, including API exposure, data movement, orchestration, logging, monitoring, security, resilience and supportability. Ensure AI services are integrated through approved enterprise patterns and governance routes</li>
</ul>
WHO YOU ARE: 
<ul>
<li>Education: Bachelor’s degree in computer science, information technology, engineering or a related field, or equivalent experience. A master’s degree or relevant specialist certifications such as TOGAF, Azure, integration platform, cloud or architecture certifications are preferred.</li>
<li>Experience: At least 10-12 years of experience in architecture, integration design or technology delivery, with significant experience in enterprise integration architecture.</li>
<li>Integration Architecture: Strong experience designing scalable, secure and loosely coupled integration architectures across cloud, SaaS, on-premise and legacy systems.</li>
<li>API Design and Management: Strong understanding of API design, API security, versioning, lifecycle management, developer experience and API management platforms.</li>
<li>Event and Messaging Architecture: Strong understanding of event-driven architecture, queues, topics, streams, pub/sub patterns, schema ownership and message reliability.</li>
<li>Integration Patterns: Experience applying integration patterns across APIs, events, messaging, batch, file exchange and orchestration.</li>
<li>Enterprise Integration Platforms: Experience with integration platforms and services such as Azure Integration Services, Azure API Management, Service Bus, Event Grid, Event Hubs, Data Factory, Apigee, MuleSoft, Boomi, SAP CPI or equivalent.</li>
<li>Cloud Integration: Experience with cloud-native and hybrid integration patterns across Azure, SaaS platforms and enterprise systems.</li>
<li>Security and Resilience: Good understanding of identity, secrets, certificates, encryption, network controls, observability, monitoring, disaster recovery and business continuity requirements.</li>
<li>Architecture Principles: Demonstrable experience of technology standards, services, design, architecture principles, architecture views, modelling and systems behaviour.</li>
<li>Solution Modelling: Knowledge of different architecture and solution modelling approaches, such as C4, UML and ArchiMate.</li>
<li>AI Integration Awareness: Understanding of the integration implications of AI systems, including secure API exposure, data movement, orchestration, auditability, monitoring and supportability.</li>
<li>Product and Delivery Methods: Strong understanding of agile delivery, programme delivery, DevOps practices and architecture governance.</li>
<li>Analytical and Problem-Solving Skills: Ability to analyse complex integration problems, develop practical options and make evidence-based recommendations.</li>
<li>Communication and Collaboration: Excellent communication and interpersonal skills, with the ability to explain integration decisions to technical and non-technical audiences.</li>
<li>Organisational Savvy: Ability to navigate organisational complexity and influence decisions across teams with different priorities.</li>
<li>AI Literacy: Ability to use approved AI tools responsibly and assess the implications of AI-enabled systems within integration architectures.</li>
</ul>
WHATS IN IT FOR YOU: 
<ul>
<li>40% staff discount plus friends & family discounts throughout the year</li>
<li>Access to our reward platform for external discount and offers</li>
<li>Private pension scheme</li>
<li>Profit related bonus scheme</li>
<li>Option to join our Healthcare Private Medical Scheme</li>
<li>Virtual GP access for you and your children – it allows you to speak to a doctor at a time and date that suits you</li>
<li>All employees are covered by our life assurance policy from day one</li>
<li>Unlock extra leave with our buy more holiday scheme.</li>
<li>Celebrate YOU! Enjoy an extra paid day off on your birthday each year</li>
<li>Enhanced maternity, paternity and adoption leave, and shared parental leave (eligible after 2 years service)</li>
<li>Spread the cost of your commute with interest-free season ticket loans</li>
<li>Do your bit for the environment and save money with our Cycle2Work scheme</li>
<li>We're proud to partner with the Retail Trust and Fashion & Textile Children's Trust</li>
</ul>
Why New Look?
 
We care about you and the planet and believe fashion should be a force for positive change. We celebrate inclusion and diversity in everything we do. We’re proud of our inclusive culture and our talented team members who embrace our shared purpose, behaviours and values.
 
We prioritise development, offering training to support your progression, so you can be your absolute best and achieve your goals.
 
We pride ourselves on being a flexible employer, our colleagues work a range of patterns. If you have a specific pattern in mind, we're keen to discuss this with you in line with the output needed for the role.
 
Please ensure that your CV is in simple format e.g. Microsoft Word when applying using your CV to ensure smooth application process

Domain Architect - Integration

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

Talan

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
As our AI practice scales, we are seeking an experienced AI Architect / Engineer to act as the senior technical authority shaping how we design and deliver next-generation AI solutions. This is a role for someone who has moved beyond building individual models to architecting entire systems: agentic platforms, LLM-powered applications, and the production infrastructure that makes them dependable at enterprise scale.
You will sit at the intersection of strategy and delivery, operating across multiple client engagements simultaneously. In the early phases you will shape solutions, validate technical approaches, and translate ambiguous business problems into robust, deployable architectures. As engagements mature, you will provide the technical oversight that keeps delivery teams aligned to the original design intent. Your influence will be felt in pre-sales conversations, solution blueprints, and the technical standards that define how our practice builds.
This is a hands on architectural role, not a purely advisory one. We expect you to remain close to the code, to prototype where it accelerates a decision, and to set a credible technical example for the engineers and data scientists you guide.
Required skills &amp; experience:<ul><li>
Lead end-to-end solution architecture for AI and LLM-based systems, spanning data, integration, infrastructure, and deployment.</li><li>
Design agentic architectures and multi-agent orchestration patterns, defining how LLMs, tools, APIs, and retrieval layers interact reliably.</li><li>
Shape early-stage engagements (scoping, solutioning, estimation, and pre-sales) turning client ambition into deliverable technical plans.</li><li>
Provide technical validation and quality oversight across several concurrent projects, mitigating risk before it reaches delivery.</li><li>
Define LLM integration and prompting strategies, including RAG, fine-tuning, evaluation, and guardrailing approaches.</li><li>
Establish MLOps and LLMOps practices that ensure solutions are observable, testable, and production ready.</li><li>
Set architectural standards, reusable patterns, and reference implementations that raise the quality bar across the practice.</li><li>
Partner with Responsible AI colleagues to embed safety, security, and governance into solution designs from the outset.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 5 years in AI architecture or AI engineering, ideally 10+, with a track record of production deployments.</li><li>
Deep expertise in LLMs, agent frameworks (e.g. LangGraph, AutoGen, Semantic Kernel), API design, and orchestration.</li><li>
Strong cloud engineering experience.</li><li>
Proven MLOps / LLMOps capability &mdash; CI/CD for models, monitoring, evaluation, and cost optimisation.</li><li>
Hands-on software engineering background (Python and modern tooling) underpinning your architectural decisions.</li><li>
Comfort managing multiple engagements at once, with pragmatic judgement on trade-offs and delivery risk.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Experience in consulting, professional services, or pre-sales environments.</li><li>
Exposure to enterprise-scale, regulated AI deployments (financial services, public sector, healthcare).</li><li>
Familiarity with vector databases, knowledge graphs, and advanced retrieval techniques.</li><li>
Relevant cloud or AI certifications.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul> 
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
You will be a founding technical voice in a practice that is investing decisively in AI. The work is varied, intellectually demanding, and commercially significant, you will shape solutions that reach production, not slideware. You will have the autonomy to define how we build, the support of a collaborative multidisciplinary team, and a clear platform to grow into a practice-leading technical figure.</div>

AI Architect / Engineer (Agentic AI & LLM Architecture)

International Swaps and Derivatives Association

<div><div>June 30, 2026
Job Title: Assistant Director, Artificial Intelligence
Reports to: Senior Director, Digital Transformation, Analytics
Location: London
</div><div>Job purpose 
This is a hands-on role. The successful candidate will architect and build production AI systems directly, while owning delivery, quality, evaluation, and partner management across the AI Solutions Lab portfolio. The role reports to the Senior Director of Digital Transformation and head of the AI Solutions Lab. 


Duties and responsibilities
<ul>
<li>Deliver the next phase of the ISDA AI Solutions Lab&rsquo;s buildout, helping move current AI initiatives from prototype/MVP stage toward robust, scalable and member-ready delivery. Architect and build the next phase of AI agents, external and internal.</li>
<li>Own the design and delivery of AI solutions that make ISDA standards and digital solutions more accessible, usable and AI-ready for members.</li>
<li>Help shape and scale the ISDA Knowledge Base and Assistant as the governed foundation for AI-enabled access to ISDA standards, taxonomies and related IP.</li>
<li>Oversee enhancement of priority AI capabilities including the CDM Coder, DRR Translator, Tracer, cross-jurisdiction analysis and AI legal opinions initiatives.</li>
<li>Help drive development and rollout of internal AI capabilities and agents aligned with the internal AI deployment roadmap.</li>
<li>Define product requirements, broader Agents orchestration, architecture direction, evaluation harnesses and quality standards and delivery priorities across the AI Solutions Lab portfolio.</li>
<li>Work closely with internal SMEs across CDM, DRR, legal, IT and product teams to ensure solutions are accurate, grounded and useful in real workflows.</li>
<li>Reach out to members for pulse checks and convert member and stakeholder feedback into roadmap decisions, product refinements and delivery choices to maximize adoption.</li>
<li>Help define practical connectivity and delivery models, including MCP servers and packaged AI Skills, so members can consume ISDA AI capabilities safely within their own environments.</li>
<li>Contribute to broader ISDA AI strategy development, including alignment between external member-facing AI solutions and internal AI deployment priorities.</li>
<li>Lead AI quality, guardrails and governance across the Lab&rsquo;s solutions, including evaluation harnesses, groundedness and traceability checks, observability and tracing, confidence frameworks, security and safe use boundaries, both internally and externally.</li>
<li>Own cost aware design of AI workloads, balancing performance and reliability against inference and infrastructure spend.</li>
<li>Manage relevant external partners and specialist vendors, ensuring work is aligned to ISDA&rsquo;s priorities, timelines, architecture and ownership model.</li>
<li>Support the Senior Director including for executive and board reporting by articulating progress, key risks, delivery needs and strategic value in a clear and concise way.</li>
<li>Help build a durable internal AI capability for ISDA that protects ISDA IP, accelerates adoption of ISDA standards and reinforces ISDA&rsquo;s strategic position in the market.</li></ul> 


Relevant Skills / Abilities
<ul>
<li>Strong senior-level experience (at least five years) leading the design and delivery of AI-enabled products or platforms from prototype through controlled rollout and production, with a demonstrable track record of shipping production AI systems that serve real users.</li>
<li>Hands-on engineering ability in Python (and ideally TypeScript/React for front end UI) and Java, and comfortable building production systems directly.</li>
<li>Deep understanding of LLMs, retrieval-augmented generation (including hybrid retrieval across semantic, graph and keyword search, with reranking and embedding-model selection), knowledge bases, knowledge graphs and ontologies, agentic workflows and skills, evaluation methods (eval harnesses, LLM-as-judge, groundedness and faithfulness metrics, tracing), and model risk controls.</li>
<li>Experience building secure, scalable and reliable AI solutions in enterprise environments, including governance, permissions, auditability and data protection including private retrieval architectures and ensuring proprietary data is not exposed to external model providers</li>
<li>Hands-on AWS experience (Bedrock, Neptune, OpenSearch, Lambda) is very important. Strong engineers able to ramp quickly will also be considered. Cost-aware design of inference and infrastructure spend is expected.</li>
<li>Proven ability to translate complex domain knowledge into usable AI products, ideally in financial markets, regulatory technology, legal tech, standards or data-intensive environments; or a demonstrated ability to ramp quickly on a complex domain.</li>
<li>Strong product and solution architecture skills, with the ability to define use cases, prioritize roadmap items and align technical delivery with strategic business outcomes.</li>
<li>Experience overseeing external vendors, technology partners and proof-of-concept work, while retaining internal control of direction, quality and IP.</li>
<li>Ability to work closely with subject matter experts to refine AI tools iteratively and turn specialist feedback into practical product improvements.</li>
<li>Strong grasp of structured data, taxonomies, ontology-style data models and mappings across complex standards or schemas.</li>
<li>Experience with user testing, controlled pilots, adoption planning, training and feedback loops for specialist user populations.</li>
<li>Strong judgment on AI risks, including hallucination, groundedness, security, explainability, confidence scoring and safe deployment boundaries.</li>
<li>Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related discipline, or equivalent practical experience, is desirable.</li>
<li>Excellent communication skills, including the ability to understand member issues, to work across the organization and influence and align stakeholders, and to brief senior management and explain technical issues in concise business language.</li>
<li>Demonstrated ability to operate in a lean, hands-on environment, balancing strategy, execution and stakeholder engagement.</li></ul></div></div>

Assistant Director, Artificial Intelligence, London

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