ai systems architect

<div>
 
 
 Department:
 
 Data &amp; AI
 
 
 
 Location:
 
 UK - London
 
 
 
 
 Description
 
 
 
 Insurance isn&rsquo;t the first industry most engineers think of when they imagine cutting-edge AI work. That&rsquo;s exactly why this role is interesting.
 
 
 CFC&rsquo;s Data &amp; AI unit is building production agentic systems that automate complex underwriting decisions - not chatbots, not copilots bolted onto legacy workflows, but autonomous multi-step AI agents that reason over unstructured data, assess risk, and drive real business outcomes. We&rsquo;re using frameworks like LangChain to orchestrate LLM-driven services that sit at the heart of how the business operates. The problems are genuinely hard: ambiguous inputs, high-stakes decisions, and the kind of domain complexity that makes for satisfying engineering.
 
 
 We&rsquo;re also fundamentally rethinking how we deliver software. We&rsquo;re moving toward an agentic-first development model - using AI agents not just in what we build for the business, but in how we build it. The goal is to multiply engineering delivery by an order of magnitude: not by cutting corners or generating throwaway code, but by designing robust systems and processes that let agents handle well-defined work while engineers focus on architecture, design, and the problems that actually require human judgment. This is a deliberate, engineering-led approach. We care about code quality, testability, and maintainability - the agent-generated code meets the same standards as everything else. We expect that a successful candidate will be able to bring their expertise to help guide and refine our agentic development process as it matures - a meaningful opportunity to influence how we work as well as what we ship.
 
 
 This is a Senior Machine Learning / AI Engineer role with genuine technical leadership scope. You&rsquo;ll shape the architecture of AI-driven production microservices, own system design decisions, and work at the intersection of traditional software engineering and applied AI. You&rsquo;ll collaborate closely with engineers, data scientists, and product managers in a team that&rsquo;s small enough for your decisions to matter and ambitious enough for the work to stay interesting.
 
 
 
 About the role
 
 
 
 <ul>
 <li>
 Design, develop, and maintain business-critical AI agent services.
 </li>
 <li>
 Build tailored agent workflows and services from business requirements, using LangChain and related frameworks with reliable patterns for LLM-driven decision-making in production.
 </li>
 <li>
 Integrate tests and validation to improve AI agents through evals and monitoring.
 </li>
 <li>
 Work with software engineers and architects to lead system design and architectural decisions.
 </li>
 <li>
 Translate technical specifications into clean, testable, and scalable production code.
 </li>
 <li>
 Work closely with cross-functional teams - engineers, data scientists, product managers - to deliver features on time and to a high standard.
 </li>
 <li>
 Write unit and integration tests to maintain reliability and service correctness.
 </li>
 <li>
 Monitor, troubleshoot, and continuously improve production services.
 </li>
 <li>
 Produce clear, structured documentation for systems, architecture, and processes.
 </li>
 <li>
 Mentor junior engineers through code reviews, best-practice guidance, and knowledge sharing.
 
 
 </li>
 </ul>
 
 About you
 
 
 
 We&rsquo;re looking for an experienced AI or Machine Learning Engineer with strong software engineering fundamentals and a passion for building robust, production-ready AI systems. You&rsquo;ll be someone who enjoys solving complex technical problems, making thoughtful architectural decisions and working on systems where quality, reliability and maintainability really matter.
 
 
 You&rsquo;ll have:
 <ul>
 <li>
 Significant experience building production-grade AI agents or LLM-powered services.
 </li>
 <li>
 Strong Python development experience, ideally with 6+ years of professional software engineering experience.
 </li>
 <li>
 A track record of writing clean, maintainable and high-quality production code.
 </li>
 <li>
 Experience supporting business-critical systems in live production environments.
 </li>
 <li>
 Strong understanding of asynchronous programming, Docker, containerised deployments and modern service architectures.
 </li>
 <li>
 Experience designing distributed systems, asynchronous microservices and event-driven architectures.
 </li>
 <li>
 Confidence leading system design discussions and making pragmatic architectural trade-offs.
 </li>
 <li>
 Strong cloud experience, ideally within Azure.
 </li>
 <li>
 Experience deploying, monitoring and maintaining ML or LLM models in production.
 </li>
 <li>
 Familiarity with MLOps, LLMOps, evals, monitoring and lifecycle management.
 </li>
 <li>
 Hands-on experience orchestrating LLM workflows using frameworks such as LangChain.
 </li>
 <li>
 An interest in how agentic software development can improve engineering delivery without compromising code quality.
 </li>
 <li>
 Strong communication skills and the ability to collaborate effectively in remote or asynchronous environments.
 </li>
 <li>
 An ownership mindset, with the ability to work independently and contribute effectively to shared codebases.
 
 
 </li>
 </ul>
 
 Core Values
 
 
 
 
 Love what you do:
 
 
 We show up each day ready to take on the world. Our passion and intensity set us apart and makes the difference to our colleagues, customers, brokers and carriers.
 
 
 
 Challenge everything:
 
 
 We&rsquo;re never afraid to question the way that things are done and we constantly challenge ourselves and others to makes things better.
 
 
 
 Have fun, be good:
 
 
 Insurance is a serious business, but we don&rsquo;t take ourselves too seriously. We make it fun to work at CFC, we welcome all viewpoints, and we treat everyone how we would expect to be treated.
</div>

Senior Machine Learning Engineer

malomatia

<div>
 
 Job Description
 
 
 
 To define technical approach to AI agents, orchestration frameworks, and responsible AI practices while working closely with engineering teams, product managers, and business stakeholders to bring cutting-edge AI capabilities to production.
 
 
 
 Responsibilities
 
 
 
 Lead AI solutions design and implementation
 
 
 <ul>
 <li>
 Serve as the primary technical advisor on generative AI initiatives
 </li>
 <li>
 Lead proof-of-concept development and architectural decision records
 </li>
 <li>
 Mentor engineering teams on agentic AI patterns and best practices
 </li>
 <li>
 Evaluate emerging technologies and maintain technical roadmaps
 </li>
 <li>
 Design and architect AI agent systems and multi-agent workflows for enterprise use cases
 </li>
 <li>
 Evaluate and implement agent frameworks including LangGraph, Microsoft Agent Framework, OpenAI Agents SDK, Google Agent-to-Agent (A2A), and emerging standard
 </li>
 <li>
 Architect tool-use patterns, function calling, MCP, and agent-to-agent communication protocols
 </li>
 <li>
 Design for agent observability, debugging, and human-in-the-loop workflows
 </li>
 <li>
 Design retrieval-augmented generation architectures and architect vector database solutions, embedding strategies, implement chunking strategies, hybrid search, and re- ranking approaches for optimal retrieval performance
 </li>
 <li>
 Design knowledge graphs and structured data integration with generative AI systems
 </li>
 <li>
 Lead architecture decisions across cloud AI platforms including Azure AI Foundry, Google Vertex AI, OpenAI APIs, and open-source Gen AI models
 </li>
 <li>
 Design prompt management, versioning, and optimization pipelines
 </li>
 <li>
 Architect for multi-model strategies, model routing, and fallback patterns
 </li>
 <li>
 Establish patterns for cost optimization, latency management, and scaling LLM workloads
 </li>
 <li>
 Define comprehensive evaluation frameworks for LLM applications and agent systems
 </li>
 <li>
 Implement automated evaluation pipelines using frameworks such as RAGAS, DeepEval, and custom evaluation harnesses
 </li>
 <li>
 Establish benchmarks for response quality, factual accuracy, task completion, and user satisfaction
 </li>
 <li>
 Champion responsible AI practices including safety, fairness, transparency, and privacy
 </li>
 <li>
 Implement guardrails, content filtering, and output validation systems
 </li>
 <li>
 Design for prompt injection prevention, data leakage protection, and secure agent execution
 </li>
 <li>
 Ensure compliance with emerging AI regulations and industry standards
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Engineering, or related field; Master's preferred. Arabic Speaker.
 </li>
 <li>
 8+ years of experience in software engineering or architecture roles
 </li>
 <li>
 3+ years of hands-on experience building LLM-powered applications in production
 </li>
 <li>
 Deep expertise in AI agent architectures, orchestration patterns, and workflow design
 </li>
 <li>
 Strong experience with at least two of the following: LangChain/LangGraph, Microsoft Semantic Kernel/Agent Framework, OpenAI Agents SDK, Google Vertex AI Agent Builder
 </li>
 <li>
 Proven experience designing and implementing Advanced RAG Systems and Agentic AI
 </li>
 <li>
 Proficiency in Python and experience with async programming patterns
 </li>
 <li>
 Hands-on experience with cloud AI platforms (Azure AI Foundry or Google Vertex AI)
 </li>
 <li>
 Strong understanding of Gen AI models&rsquo; fundamentals including prompting, fine-tuning, context windows, and token economics
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience implementing Model Context Protocol (MCP), Google Agent-to-Agent (A2A) protocol, and multi-agent communication patterns
 </li>
 <li>
 Experience building AI Evals pipelines and AI quality assurance systems
 </li>
 <li>
 Knowledge of advanced RAG techniques: query decomposition, multi-hop reasoning, GraphRAG
 </li>
 <li>
 Experience with AI observability tools
 </li>
 <li>
 Background in AI safety, red-teaming, or responsible AI implementation.
 
 
 </li>
 </ul>
 Skills &amp; Competencies
 
 
 <ul>
 <li>
 Systems thinking with ability to design for complexity and emergence in agentic systems
 </li>
 <li>
 Strong communication skills to convey AI concepts to diverse audiences
 </li>
 <li>
 Pragmatic approach balancing innovation with production readiness
 </li>
 <li>
 Ability to rapidly learn evolving AI technologies
 </li>
 <li>
 Commitment to ethical AI development and user safety
 </li>
 <li>
 Collaborative mindset with ability to influence across organizational boundaries
 
 
 </li>
 </ul>
 
 About Malomatia
 
 
 
 
 ABOUT US
 
 
 
 malomatia is a leading Qatar-based IT services and solutions provider, bringing together top Qatari and international talent to deliver innovative, end-to-end technology solutions that empower clients to achieve their strategic goals.
 
 
 
 Our mission
 
 
 
 Empowering Qatar&rsquo;s businesses and governments to leap into the digital future with agile, knowledge-driven solutions.
 
 
 
 Our vision
 
 
 
 To become Qatar&rsquo;s trusted knowledge partner in digital transformation, disrupting industries, shaping the future, and building a world-class tech ecosystem.
 
 
 
 Driving change that makes a real impact
 
 
 
 Since 2008, malomatia has been driving Qatar&rsquo;s digital transformation through innovative, ISO-certified IT solutions. With expertise across key public and private sectors, we empower the nation&rsquo;s vision with advanced services in cloud, cybersecurity, AI, and contact center excellence, elevating the role of technology in shaping Qatar&rsquo;s sustainable future.
 
 
 
 About The Team
 
 
 
 Established in 2008, malomatia is a Qatari leader in IT services and digital transformation. We serve key sectors including Government, Healthcare, Education, Customs, and Transportation, delivering impactful solutions that support national development goals. Powered by a diverse team of skilled Qatari and international IT professionals, we deliver innovative, high-value digital solutions tailored to the unique needs of our clients.
 
 
 Our mission is to inspire customers to thrive through digital excellence, and we envision becoming the trusted partner of choice in building a smarter society through technology and talent. We are driven by core values that define our culture and approach: ownership, integrity, empathy, teamwork, transparency, agility, excellence, trust, and innovation.
 
 
 Join us in shaping the future of technology in Qatar
</div>

Senior Consultant - AI Solution Architect

Accenture

Project Role Description: Automation Architect should be able to drive/design/solution end-to-end AI-powered automation solutions leveraging Generative AI and Agentic AI Technologies across client ecosystems (Claude, OpenAI, Google Gemini) for External & Internal Accenture stakeholders.
 
Must have skills: 
1. Overall 7+ years of experience in IT Industry with extensive experience in delivering/architecting AI, Gen AI, and Agentic AI automation solutions across Application Maintenance / Application Development/ System Integration/Transformation engagements.
 2. 2+ Years of experience leading teams as Technical Lead/Solution Architect on AI-led automation programmes.
 3. Ability to understand & architect multi-agent orchestration frameworks, RAG pipelines, and LLM-integrated automation workflows leveraging modern architecture principles.
 4. Design, develop and architect automation solutions using RPA/AI/Gen AI/Agentic AI platforms (Anthropic Claude, OpenAI, Google Gemini), integrated with enterprise systems i.e. ERP, ITSM, CRM and Cloud platforms (AWS/Azure/GCP), leveraging modern delivery methods i.e. Agile, DevOps etc.
 5. Industry domain exposure in Financial Services, Retail & CPG, Life Sciences, Aerospace/Manufacturing, or Managed Services/AMS.
 6. Understanding of Integration Architectures, Observability/AIOps Architectures (Dynatrace, Datadog, ServiceNow), and Data/RAG Architectures.
 
Good to Have skills: 
7. Experience in solution architecting in shaping/responding RFP & RFI Pursuits, including Techno-Functional & Commercial aspects of the solution.
 8. Cloud Certification in any CSP i.e. AWS/Azure/GCP.
 9. Prompt Engineering, AI/ML Technical Certifications, Industry SME knowledge, or Generative AI Platform certifications are good to have skills.
 
Key Responsibilities: 
10. Lead client conversations & internal engineering discussions for solutioning complex automation requirements and reusable asset/accelerator development.
 11. Provide technical solutions for client Proof of Concepts; plan the overall pursuit, gather requirements, execute and manage Gen AI/Agentic AI automation solutions in response to a Client Request/RFP/Delivery Optimization initiative.
 12. Co-ordinate & work with technical teams for client deployments, automation pipeline testing, and product enhancements; govern delivery against approved architecture baselines.
 
Professional Attributes: 
7-12 years of experience in IT industry experience in technology consulting/Application Services, system integration, outsourcing, or cloud advisory services.
 Outstanding interpersonal/communication skills, strong articulation capability, ability to influence and build relationships with clients and key stakeholders; structured, issue-based problem-solving approach.
 Ability to understand client business and technology drivers - business-IT alignment, AI/automation operating model, and sourcing model dimensions.
 In-depth expertise and prior experience; ITIL/PMP/TOGAF/Generative AI certifications preferable.
 Educational Qualification: Engineering Bachelor's degree from premier Tier-1/2 institute / Masters / Diploma in Management.
 
TBD

IMS Solution Architecture Manager

Nagarro

<div>
 
 Job Description
 
 
 
 Must have Skills : Architecture (Strong), Cloud architecture (Strong), Technology Architect - Data Architecture (Strong), Technology Architect - Generative AI,
 
 
 Experience: 12+ Years Role Overview We are seeking a seasoned Enterprise &amp; Solution Architect with strong cross-domain expertise and deep technology capabilities to drive large-scale digital transformation initiatives. The role requires a strategic thinker with hands-on architecture experience across industries such as Telecom, Energy, Public Sector, and BFSI, combined with strong proficiency in modern technology stacks including cloud, web, and advanced Data &amp; AI.
 
 
 Key Responsibilities - Define and drive enterprise architecture strategy aligned with business goals across multiple industry domains (Telco, Energy, Public Sector, BFSI). - Lead end-to-end solution architecture for large, complex transformation programs, ensuring scalability, security, and performance. - Design and govern data-driven architectures, including data platforms, analytics ecosystems, and AI/ML solutions. - Architect and implement solutions leveraging Cloud (OCI/AWS/Azure/GCP), Microservices, APIs, and Modern Web Technologies. - Drive adoption of AI capabilities, including Machine Learning, Generative AI, and emerging Agentic AI frameworks for enterprise use cases. - Establish architecture governance, standards, and best practices across programs and portfolios. - Collaborate with business stakeholders to translate requirements into scalable and future-ready architecture blueprints. - Provide technical leadership across delivery teams, ensuring alignment with architecture vision and quality benchmarks. - Evaluate and recommend technology platforms, tools, and vendors aligned with enterprise strategy. - Lead solutioning for RFPs, proposals, and client engagements, including effort estimation and technical strategy.
 
 
 Key Skills &amp; Competencies Domain Expertise - Strong understanding of at least two or more domains: o Telecom (BSS/OSS, Digital Channels) o Energy &amp; Utilities o Public Sector (eGov, Smart City) o BFSI (Banking, Payments, Insurance) Technology Expertise - Cloud Platforms: AWS, Azure, or GCP (multi-cloud exposure preferred) - Architecture Patterns: Microservices, Event-driven, API-first, Domain-driven design - Web Technologies: Modern front-end and backend frameworks - Integration: APIs, Middleware, ESB, iPaaS Data &amp; AI (Core Focus) - Strong expertise in Data Architecture (Data Lakes, Data Warehouses, Lakehouse) - Hands-on experience with Machine Learning models and lifecycle management (MLOps) - Experience in Generative AI (LLMs, prompt engineering, RAG architectures) - Exposure to Agentic AI systems (autonomous agents, orchestration frameworks) - Knowledge of data governance, security, and privacy frameworks
 
 
 Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, or related field - Architecture certifications (TOGAF, Cloud Architect certifications) preferred
 
 
 Leadership &amp; Behavioral Skills - Strong stakeholder management and executive communication skills - Ability to operate at both strategic and hands-on levels - Proven experience in leading distributed and cross-functional teams - Strong problem-solving and decision-making capabilities
</div>

ENTERPRISE ARCHITECT

Tandem Search

<div>
 
 Principal Computer Vision &amp; AI Engineer
 
 
 
 Location:
 
 Al Khobar, Saudi Arabia
 
 
 
 
 
 Role Overview
 
 
 We are looking for a highly experienced
 
 Principal Computer Vision &amp; AI Engineer
 
 to lead the technical direction of production AI systems operating over
 
 live video streams in real-world environments
 
 .
 
 
 
 
 
 This is a hands-on technical leadership role rather than a people-management position. You will architect, build, optimise and deploy advanced
 
 computer vision, video understanding and multimodal/Vision-Language Model (VLM)
 
 systems while providing technical direction to senior engineers.
 
 
 
 
 
 Key Responsibilities
 
 <ul>
 <li>
 Architect and build production
 
 computer vision and video analytics systems
 
 .
 </li>
 <li>
 Develop solutions across
 
 object detection, segmentation, tracking, event understanding and spatial reasoning
 
 .
 </li>
 <li>
 Design and deploy
 
 VLM/multimodal AI systems
 
 operating over live and recorded video.
 </li>
 <li>
 Own the full ML lifecycle: data strategy, experimentation, fine-tuning, evaluation, deployment and monitoring.
 </li>
 <li>
 Optimise models for
 
 edge and cloud inference
 
 , balancing accuracy, latency, throughput and cost.
 </li>
 <li>
 Establish automated model evaluation, regression testing and production monitoring.
 </li>
 <li>
 Develop agentic AI systems capable of reasoning over video and interacting safely with tools, APIs, cameras and sensors.
 </li>
 <li>
 Set technical architecture and engineering standards while remaining highly hands-on with code.
 </li>
 </ul>
 
 
 
 
 What We're Looking For
 
 <ul>
 <li>
 Deep hands-on experience in
 
 Computer Vision / Video AI
 
 .
 </li>
 <li>
 Strong production experience working with
 
 live or streaming video
 
 .
 </li>
 <li>
 Strong
 
 PyTorch and/or TensorFlow
 
 experience.
 </li>
 <li>
 Expertise across detection, segmentation and tracking using technologies such as
 
 YOLO, DETR/RT-DETR, GroundingDINO or equivalent
 
 .
 </li>
 <li>
 Production experience with
 
 Vision-Language Models / multimodal models
 
 such as Qwen-VL, InternVL, LLaVA, Gemini or equivalent.
 </li>
 <li>
 Experience deploying and optimising AI models in production.
 </li>
 <li>
 Exposure to
 
 edge AI
 
 , ideally TensorRT, ONNX Runtime, NVIDIA Jetson or similar.
 </li>
 <li>
 Strong understanding of model evaluation, MLOps, active learning and production monitoring.
 </li>
 <li>
 Ability to operate as a
 
 Principal/Staff-level technical authority
 
 while remaining hands-on.
 </li>
 </ul>
 
 Nice to Have
 
 <ul>
 <li>
 Agentic AI / tool-calling systems such as LangGraph, LangChain or equivalent.
 </li>
 <li>
 Real-time CCTV, camera or video-streaming systems.
 </li>
 <li>
 Industrial, construction, robotics, autonomous systems or safety-critical AI experience.
 </li>
 <li>
 RAG / multimodal retrieval and vector search.
 </li>
 <li>
 Self-hosted VLM/LLM serving such as vLLM or NIM.
 </li>
 </ul>
 
 
 Critical requirement:
 
 Candidates must have substantial hands-on experience with
 
 video-based computer vision systems
 
 . Pure GenAI/LLM profiles without strong production video/CV experience will not be suitable.
 
</div>

Principal AI Engineer

NewRocket

<div>Agentic AI Architect-Anthropic Partnership

Why Us

NewRocket is proud Anthropic partner/vendor, expanding our ability to help enterprises responsibly adopt and operationalize Claude-powered AI solutions. Through this relationship, NewRocket is building advanced capabilities in generative AI, agentic workflows, secure enterprise knowledge experiences, and AI-enabled automation. Our teams apply Anthropic-aligned practices in prompt and context engineering, retrieval-augmented generation (RAG), tool use, structured outputs, model evaluation, safety, governance, and human-in-the-loop controls.

For an Agentic AI Architect, this partnership represents an opportunity to work at the forefront of enterprise AI&mdash;designing scalable, secure, and high-value solutions that connect Claude and other AI technologies with ServiceNow, enterprise data, business processes, and mission-critical workflows.

NewRocket is the AI-first Elite ServiceNow Partner that activates real value on the Now Platform. As a trusted advisor to enterprise leaders, we combine industry expertise, human-centered design, and enterprise-grade AI to help organizations navigate change and scale with confidence.

Travel to clients and conferences as needed.

We #GoBeyondWorkflows to create new kinds of experiences for our customers.

Come join our Crew!

The Role

NewRocket is hiring an experienced Agentic AI Architect to support a large global client and help shape, design, and deploy enterprise AI solutions.

This role combines AI/ML architecture, generative AI engineering, data engineering, cloud solution design, and technical leadership. You will be responsible for defining scalable architectures for AI and machine learning applications, including predictive analytics, natural language processing, retrieval-augmented generation (RAG), intelligent automation, and agentic AI systems.

The ideal candidate brings strong hands-on expertise in Python, SQL, cloud services, databases, big-data technologies, and modern machine learning frameworks. You will also have practical experience designing LLM-powered applications that safely connect models to enterprise knowledge, systems, APIs, and workflows.

You will work closely with client stakeholders, NewRocket consultants, ServiceNow teams, data engineers, and AI/ML engineers to translate business needs into secure, reliable, and production-ready AI solutions.

We are #GoingBeyond. Come join our Crew!

What You Will Be Doing

AI/ML Architecture &amp; Solution Delivery
<ul>
<li>Architect, develop, deploy, and maintain scalable AI and machine learning solutions for enterprise use cases.</li>
<li>Define end-to-end solution architectures spanning data ingestion, data preparation, model selection, orchestration, APIs, workflow integrations, user experiences, monitoring, and governance.</li>
<li>Partner with business and technical stakeholders to identify high-value AI opportunities and translate requirements into actionable technical designs and delivery roadmaps.</li>
<li>Design solutions for predictive analytics, classification, clustering, forecasting, anomaly detection, recommendation, and intelligent automation.</li>
<li>Establish technical standards, reference architectures, reusable patterns, and best practices for enterprise AI delivery.</li>
<li>Lead technical discovery, architecture workshops, design reviews, proof-of-concepts, and client demonstrations.</li>
</ul>
Generative AI, Anthropic &amp; LLM Engineering
<ul>
<li>Design and implement enterprise generative AI applications using Claude, the Anthropic API, and other LLM platforms when appropriate for the business use case.</li>
<li>Apply effective prompt and context-engineering practices, including instruction design, few-shot examples, role definition, structured inputs and outputs, response constraints, and long-context management.</li>
<li>Architect retrieval-augmented generation (RAG) solutions that securely ground model outputs in approved enterprise documents, knowledge bases, databases, and other data sources.</li>
<li>Design document ingestion, chunking, embedding, vector search, retrieval, reranking, citation, and response-generation patterns for enterprise knowledge workflows.</li>
<li>Build and integrate AI capabilities using structured outputs, tool use/function calling, APIs, and workflow orchestration.</li>
<li>Assess and recommend the appropriate balance of LLMs, traditional machine learning, deterministic automation, enterprise search, and human decision-making for each use case.</li>
<li>Stay current on Anthropic platform capabilities, Claude releases, Anthropic implementation guidance, responsible AI principles, and enterprise AI best practices.</li>
<li>Complete relevant Anthropic partner enablement, technical training, and product education as available through NewRocket's partnership.</li>
<li>Travel to clients and conferences as needed.</li>
</ul>
Agentic AI &amp; Workflow Orchestration
<ul>
<li>Architect and implement agentic AI systems that can reason over enterprise context, use authorized tools, execute multi-step tasks, and coordinate work across enterprise applications.</li>
<li>Design AI agents with defined roles, task boundaries, tool permissions, memory and context strategies, approval gates, fallback paths, and escalation mechanisms.</li>
<li>Develop agentic workflows that integrate with ServiceNow, enterprise APIs, cloud services, databases, collaboration platforms, and operational systems.</li>
<li>Implement human-in-the-loop controls for sensitive, high-impact, low-confidence, or exception-based actions.</li>
<li>Design safeguards to prevent unintended tool execution, unauthorized data access, prompt injection, unsafe outputs, and uncontrolled autonomous behavior.</li>
<li>Evaluate agent effectiveness through task-completion rates, quality, reliability, latency, cost, safety, and user-adoption measures.</li>
</ul>
Machine Learning, NLP &amp; Data Science
<ul>
<li>Develop, train, validate, deploy, and monitor machine learning models for predictive analytics, classification, clustering, and related use cases.</li>
<li>Implement AI and ML solutions using frameworks such as TensorFlow, PyTorch, and Scikit-learn.</li>
<li>Develop NLP capabilities using Hugging Face transformer models and cloud AI services for text classification, summarization, sentiment analysis, entity extraction, and document intelligence.</li>
<li>Evaluate, adapt, and where appropriate fine-tune open-source or client-approved models for targeted use cases; apply prompt engineering, RAG, and tool use as preferred strategies when model fine-tuning is not appropriate or available.</li>
<li>Work with large language models for conversational AI, text generation, summarization, knowledge assistance, workflow automation, and decision support.</li>
<li>Build data-processing and feature-engineering pipelines that support reliable model training, testing, deployment, and monitoring.</li>
</ul>
Cloud, Data Engineering &amp; Platform Integration
<ul>
<li>Design and implement AI solutions using cloud platforms including AWS (e.g., SageMaker, Lambda, S3), Microsoft Azure, and Google Cloud Platform (e.g., Vertex AI).</li>
<li>Develop integrations between AI services, ServiceNow, enterprise applications, APIs, identity providers, databases, document repositories, and data platforms.</li>
<li>Build supporting services, APIs, microservices, automation logic, and integration components required to operationalize AI solutions.</li>
<li>Work with big-data technologies such as Apache Spark and Snowflake for large-scale data processing, analytics, and AI data pipelines.</li>
<li>Design and optimize ETL/ELT pipelines for data ingestion, transformation, validation, quality management, governance, and observability.</li>
<li>Use SQL, MySQL, PostgreSQL, MongoDB, and comparable technologies for data modeling, database management, query optimization, and data warehousing.</li>
<li>Apply secure engineering practices for authentication, authorization, secrets management, encryption, logging, error handling, and access controls.</li>
</ul>
AI Quality, Governance &amp; Responsible AI
<ul>
<li>Establish evaluation frameworks, test suites, representative datasets, and regression-testing practices for AI, ML, and agentic solutions.</li>
<li>Measure and optimize solution quality across relevance, accuracy, groundedness, safety, task completion, model behavior, latency, cost, reliability, and user experience.</li>
<li>Implement observability, monitoring, tracing, alerting, and feedback loops for production AI applications.</li>
<li>Define practical governance approaches for data privacy, sensitive-data handling, model access, auditability, model limitations, and responsible AI usage.</li>
<li>Implement controls for role-based access, data permissions, grounded responses, source attribution, output validation, exception handling, and human review.</li>
<li>Document architecture decisions, AI-system behavior, limitations, risk controls, operating procedures, and support requirements.</li>
</ul>
ServiceNow, Automation &amp; Enterprise Experience
<ul>
<li>Design AI-enabled workflow automations and intelligent experiences within ServiceNow and connected enterprise ecosystems.</li>
<li>Support chatbot, virtual-agent, employee-support, customer-service, IT operations, knowledge-management, and workflow-automation use cases.</li>
<li>Integrate AI solutions with ServiceNow capabilities such as workflow automation, IntegrationHub, Flow Designer, Virtual Agent, Now Assist, AI Agents, knowledge management, and enterprise data sources, where applicable.</li>
<li>Develop AI automation solutions using collaboration platforms and cloud AI services, including Microsoft Teams and Azure AI, where appropriate.</li>
<li>Contribute reusable implementation patterns, agent designs, integration components, evaluation assets, and accelerators that strengthen NewRocket's AI Foundry capabilities.</li>
</ul>
Analytics &amp; Visualization
<ul>
<li>Create interactive data visualizations and executive-ready reporting using tools such as Tableau and Power BI.</li>
<li>Develop dashboards and measurement frameworks that help stakeholders understand AI adoption, workflow outcomes, business value, operational performance, and model quality.</li>
<li>Support the definition and tracking of KPIs that demonstrate measurable value from AI-enabled solutions.</li>
</ul>
What You Bring Along
<ul>
<li>10+ years of experience applying AI, machine learning, data science, software engineering, or intelligent automation technologies to practical enterprise use cases.</li>
<li>Strong coding expertise in Python and SQL, with hands-on experience using ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.</li>
<li>Demonstrated experience architecting or delivering AI/ML, LLM, RAG, conversational AI, agentic AI, or AI-powered automation solutions.</li>
<li>Strong understanding of algorithms, object-oriented programming, functional design principles, software architecture, and API-based integration patterns.</li>
<li>Hands-on experience with LLM concepts and application-development patterns, including prompt engineering, context management, tokens, embeddings, vector search, RAG, tool use, structured outputs, and model evaluation.</li>
<li>Proficiency with data-science libraries such as Pandas, NumPy, Matplotlib, and Seaborn.</li>
<li>Hands-on experience with cloud platforms such as AWS, Azure, and/or Google Cloud.</li>
<li>Experience with big-data processing and cloud data platforms, including Apache Spark and Snowflake.</li>
<li>NLP experience using Hugging Face, transformer models, cloud AI services, or comparable technologies.</li>
<li>Strong understanding of database management, query optimization, data warehousing, ETL/ELT pipelines, and data-quality practices.</li>
<li>Experience with data visualization tools such as Tableau and Power BI.</li>
<li>Knowledge of responsible AI practices, including privacy, security, human oversight, hallucination mitigation, prompt-injection defenses, model limitations, and governed deployment.</li>
<li>Strong analytical, architectural, problem-solving, communication, and stakeholder-management skills.</li>
<li>Ability to collaborate effectively across client, consulting, engineering, product, data, and AI/ML teams.</li>
<li>Ability to learn and adapt quickly as AI technologies, enterprise requirements, and client needs evolve.</li>
</ul>
Preferred Qualifications

Anthropic &amp; Claude Experience
<ul>
<li>Hands-on experience with Claude, the Anthropic API, Anthropic Console, Claude Code, or Anthropic-focused implementation guidance.</li>
<li>Completion of Anthropic Academy courses, partner enablement, technical training, or equivalent experience building Claude-powered enterprise applications.</li>
<li>Experience using Claude capabilities such as long-context processing, document analysis, tool use, structured outputs, and enterprise knowledge workflows.</li>
<li>Familiarity with Model Context Protocol (MCP) concepts and secure patterns for connecting AI applications to enterprise tools and data sources.</li>
</ul>
Agentic AI &amp; LLM Operations
<ul>
<li>Experience designing AI agents, multi-agent systems, AI orchestration workflows, and human-in-the-loop operating models.</li>
<li>Experience with LLM application frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or comparable frameworks.</li>
<li>Experience with vector databases, semantic retrieval, enterprise search, embeddings, document ingestion, reranking, and RAG evaluation.</li>
<li>Familiarity with AI observability, tracing, prompt/version management, evaluation frameworks, guardrails, model monitoring, and cost optimization.</li>
<li>Experience with MLOps, LLMOps, CI/CD, Docker, Kubernetes, infrastructure as code, and production cloud deployment practices.</li>
</ul>
Education
<ul>
<li>Bachelor's degree in Computer Science, Data Science, Artificial Intelligence/Machine Learning, Engineering, or a related technical field; equivalent relevant experience will also be considered.</li>
<li>Advanced degree or relevant AI, cloud, data, ServiceNow, or Anthropic certifications are a plus.</li></ul> 


We Take Care of Our People

NewRocket is committed to a diverse and inclusive workplace. We value and celebrate diversity, believing that every employee matters and should be respected and heard. We are proud to be an equal opportunity workplace and affirmative action employer, committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin, or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, citizenship, military, or Veteran status. For individuals with disabilities who would like to request an accommodation, please contact hr.in@newrocket.com.</div>

Agentic AI Architect-Anthropic-UK

FalconSmartIT

<div>Job Title : Enterprise Architect - Banking Transformation, Cloud &amp; AI
Job Location :London, UK (4 days per week from office)
Job Type: FTE 
 
Job Description : 
 
About the Role
We are undertaking a significant transformation of the Bank and are reimagining how we build a genuinely modern, intelligent banking platform for the future. This transformation spans Payments, FX, Data, Cloud, and AI, and will redefine both our technology landscape and future operating model.
This is a high-impact leadership role for an experienced Enterprise Architect who has successfully led large-scale banking transformations and can bridge the gap between strategic vision and practical execution. We're not seeking someone who governs architecture from the sidelines. We need a hands-on architectural leader who can shape the future direction of the Bank, challenge traditional thinking, and work closely with engineering and transformation teams to deliver tangible outcomes.
A key aspect of this role is helping to define how emerging technologies, including AI, agentic architectures, intelligent orchestration, and automation, can be leveraged to create the next generation of banking capabilities.
Key Responsibilities
Enterprise Architecture Leadership
<ul><li>Define and own the Bank's end-to-end enterprise architecture strategy and roadmap.</li>
<li>Establish architectural principles, standards, and target-state technology architectures across business and technology domains.</li>
<li>Align technology investments with strategic business objectives and regulatory requirements.</li>
<li>Proven experience leading enterprise architecture functions within banking or financial services.</li>
<li>Demonstrated success delivering large-scale technology transformation programmes.</li>
<li>Deep domain expertise in one or more of:</li>
<li>Banking platforms</li>
<li>Payments</li>
<li>FX and Treasury systems</li>
<li>High-volume transaction processing environments</li>
<li>Strong understanding of both legacy and modern technology estates.</li>
<li>Significant experience designing and implementing:</li>
<li>Event-driven architectures</li>
<li>Distributed systems</li>
<li>Cloud-native solutions</li>
<li>API ecosystems</li>
<li>Experience working within highly regulated environments.</li>
<li>Track record of influencing and partnering with executive-level stakeholders.</li>
</ul>Desired Experience
<ul><li>Experience with multi-cloud environments (Azure, AWS, GCP).</li>
<li>Knowledge of AI, Generative AI, Agentic AI frameworks, and intelligent automation.</li>
<li>Experience defining target operating models and business capability architectures.</li>
<li>Familiarity with data mesh, real-time analytics, and enterprise data platforms.</li>
<li>Understanding of modern banking ecosystem trends, open banking, and embedded finance.</li>
</ul>Skills &amp; Competencies
<ul><li>Strategic thinking with strong execution focus.</li>
<li>Exceptional stakeholder management and influencing skills.</li>
<li>Strong leadership presence and communication abilities.</li>
<li>Commercial and business acumen.</li>
<li>Ability to navigate ambiguity and drive organizational change.</li>
<li>Deep understanding of technology risk, security, and regulatory considerations.</li>
<li>Passion for innovation and the future of AI-enabled banking</li></ul></div>

Enterprise Architect - Banking Transformation, Cloud & AI

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