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ai data scientists (cctv analytics) Jobs in Abu Dhabi

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business analyst – data & analytics Jobs in Abu Dhabi

business analyst – data & analytics

data science expert

data analytics architect

Confidential

<div>
 
 We're excited to be partnering with a leading institution in the UAE that is building a digital-first, AI-enabled financial services organisation from the ground up. This is a unique opportunity to join at an early stage and help shape the technology, data, and AI foundations of a business with significant institutional backing and long-term ambition. If you're passionate about data architecture, AI-ready platforms, and creating enterprise-wide data strategies, we'd love to hear from you.
 
 
 As Data Architect, you will be responsible for defining the bank's data strategy, target-state architecture, data products, and AI-ready data ecosystem. Working closely with Data Engineering, Data Governance, AI Engineering, Enterprise Architecture, and business stakeholders, you'll help establish the trusted data foundation that powers analytics, AI, regulatory reporting, and ecosystem-wide data sharing from day one.
 
 
 
 
 
 
 Responsibilities
 
 
 
 &bull; Define and maintain the bank's enterprise data strategy, target-state architecture, and data models across all business domains.
 
 
 &bull; Design AI-ready data foundations, including feature pipelines, vector-ready architectures, semantic layers, and end-to-end lineage.
 
 
 &bull; Establish the bank's data product architecture, operating model, data contracts, and interoperability standards.
 
 
 &bull; Design data-sharing architectures and ecosystem exchange patterns across internal and external stakeholders.
 
 
 &bull; Define metadata, semantic, ontology, and master data management frameworks across the organisation.
 
 
 &bull; Provide architecture leadership, challenge vendor designs, and ensure the target architecture is adopted across delivery teams.
 
 
 
 
 
 
 Requirements
 
 
 
 &bull; 10+ years of experience in Data Architecture within banking, financial services, or another highly regulated environment.
 
 
 &bull; Proven experience designing enterprise data platforms that support AI, machine learning, and analytics workloads.
 
 
 &bull; Strong expertise in cloud-based data architectures, lakehouse platforms, streaming architectures, and governed data services.
 
 
 &bull; Experience defining data products, semantic models, metadata architectures, and enterprise data standards.
 
 
 &bull; Strong knowledge of banking regulatory requirements including BCBS 239, data governance, and data protection frameworks.
 
 
 &bull; Experience designing ecosystem-wide data-sharing capabilities, Open Finance architectures, or enterprise-scale integration models.
 
 
 
 
 
 Ready to join us? Apply today and take the next step in your career.
 
</div>

Data Architect

Damen Middle East

Data &amp; AI Transformation ArchitectAbu Dhabi, UAE | Full-TimeReady to help shape the future of Data &amp; AI in a global maritime organization?Damen is looking for an experienced Data &amp; AI Transformation Architect to help accelerate our journey toward becoming a truly data-driven and AI-enabled enterprise. This is a hands-on, strategic role focused on Data Architecture, Data Governance, Enterprise Data Modelling, Master Data Management (MDM), and modern Data &amp; AI platforms.What You'll Do<ul><li>Lead enterprise Data &amp; AI transformation initiatives</li><li>Develop and improve enterprise data architecture and governance frameworks</li><li>Design and evolve conceptual, logical, and physical data models</li><li>Drive adoption of Data Governance, MDM, and AI best practices</li><li>Collaborate with business and technology stakeholders globally</li><li>Help shape Damen's future Data &amp; AI platform and operating model</li></ul>What We're Looking For<ul><li>10+ years of experience in Data Architecture, Data Governance, MDM, Data Management, or Data Transformation</li><li>Strong experience with Enterprise Data Modelling</li><li>Hands-on experience with Microsoft Azure, Fabric, Databricks, Purview, or similar technologies</li><li>Experience in manufacturing, marine, shipbuilding, engineering, construction, energy, utilities, or other asset-intensive industries</li><li>Strong stakeholder management and consulting skills</li><li>Experience driving enterprise-wide transformation and data maturity programs.</li></ul>Why Join Damen?Join a global organisation investing heavily in Data, AI, and digital transformation. You'll work with international stakeholders, influence strategic initiatives, and play a key role in building a world-class Data &amp; AI capability that supports the future of the maritime industry.Pay: AED15,000.00 - AED20,000.00 per monthApplication Question(s):<ul><li>Has your experience been primarily limited to reporting, dashboards, business analysis, or data science without responsibility for enterprise architecture or governance? </li></ul>Experience:<ul><li>Data Architecture transformation programme: 5 years (Required)</li><li>Enterprise Data: 5 years (Required)</li></ul>Work Location: In person

Data & AI Transformation Architect

AppliedAI

<div>
 
 
 AI Solutions Consultant
 
 
 
 On-site | Abu Dhabi
 
 
 
 
 
 AppliedAI is a pioneering AI technology company headquartered in Abu Dhabi, UAE. We are committed to innovation and excellence in artificial intelligence solutions across regulated industries such as healthcare, insurance, government, and financial services.
 
 
 
 
 
 AppliedAI is at the forefront of redefining the future of work through cutting-edge AI solutions. We empower organizations by automating complex, document-heavy processes, ensuring unparalleled efficiency and accuracy.
 
 
 
 
 
 Our commitment to synergizing human intelligence with artificial intelligence helps our clients excel in highly regulated industries, including healthcare, finance, and insurance.
 
 
 
 
 
 
 Role Overview:
 
 
 
 
 
 
 We are seeking a Solutions Consultant to join our growing post-sales Delivery Team, responsible for ensuring client success with our agentic AI workflow orchestration platform,
 
 Opus
 
 .
 
 
 
 
 
 In this role, you will work directly with enterprise clients after the sale to translate requirements into detailed technical designs and guide implementation.
 
 
 
 
 
 You&rsquo;ll demonstrate strong technical confidence and analytical skills, and will have the ability to balance solution design with hands-on technical oversight and stakeholder management.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 
 
 Client Engagement &amp; Discovery
 
 
 
 
 
 <ul>
 <li>
 Lead deep-dive discovery sessions to identify needs and drivers beyond surface-level requirements.
 </li>
 <li>
 Partner with client teams to define workflows and align on architecture decisions while building internal advocates and champions.
 </li>
 <li>
 Build trusted technical relationships with client stakeholders, acting as a go-to adviser for orchestration design.
 </li>
 <li>
 Navigate complex organizational dynamics to ensure alignment between IT and Operations.
 </li>
 </ul>
 
 
 
 
 
 Solution Design &amp; Documentation
 
 
 
 
 
 <ul>
 <li>
 Architect business cases that quantify ROI and P&amp;L impact to create urgency for change.
 </li>
 <li>
 Define integration points with client systems including APIs, data sources, and cloud infrastructure.
 </li>
 <li>
 Maintain design decision logs, system interface definitions, and solution playbooks for each engagement.
 </li>
 </ul>
 
 
 
 
 
 Technical Leadership
 
 
 
 
 
 <ul>
 <li>
 Provide deep technical guidance to both Provide clear and actionable instructions to client teams and internal implementation engineers.
 </li>
 <li>
 Identify and resolve technical blockers and system constraints during the delivery phase.
 </li>
 </ul>
 
 
 
 
 
 Outcome-Focused Delivery
 
 
 
 
 
 <ul>
 <li>
 Conduct demonstrations that focus on business outcomes rather than just feature tours.
 </li>
 <li>
 Serve as an escalation point for complex technical challenges during delivery.
 </li>
 </ul>
 
 
 
 
 
 Key Requirements:
 
 
 
 
 
 
 Experience:
 
 
 
 
 <ul>
 <li>
 5+ years in solutions consulting, technical consulting, or technical business analysis roles.
 </li>
 <li>
 Proven post-sales experience working directly with enterprise clients
 </li>
 <li>
 Strong background in workflow automation, distributed systems, or AI/ML-driven platforms.
 </li>
 </ul>
 
 
 
 
 Technical Skills:
 
 
 
 
 <ul>
 <li>
 Technical Confidence:Expert in discussing AI, APIs, and integrations (e.g., webhooks) without requiring regular engineering support.
 </li>
 <li>
 Requirements Engineering:Expert in translating vague use cases into robust technical solutions and sequence diagrams.
 </li>
 </ul>
 
 
 
 
 Soft Skills:
 
 
 
 
 <ul>
 <li>
 Effective Stakeholder Engagement: Ability to re-frame scepticism and stay calm when challenged by stakeholders.
 </li>
 <li>
 Executive Presence: Comfortable challenging C-suite thinking and shifting from features to strategic impact.
 </li>
 <li>
 Collaborative Mindset: Able to interface effectively with client engineers, architects, and executives.
 </li>
 </ul>
 
 
 
 
 
 What We Offer:
 
 
 
 
 
 <ul>
 <li>
 Opportunity to shape the marketing analytics strategy at a leading AI company.
 </li>
 <li>
 Exposure to cutting-edge AI/ML applications in real-world business contexts.
 </li>
 <li>
 Collaborative, innovative, and growth-driven work environment.
 </li>
 <li>
 Competitive compensation, benefits, and career advancement opportunities.
 </li>
 </ul>
</div>

AI Solutions Consultant

e7 Group

<div>
 Job description:
 
 
 
 
 Senior Specialist - AI and Data Analytics
 
 
 
 We are seeking an experienced
 
 Senior Specialist - AI and Data Analytics
 
 to lead the development of AI-driven solutions, advanced analytics, and business intelligence capabilities across e7 Group. This role will transform enterprise data into actionable insights, enabling data-driven decision-making, operational excellence, and digital transformation initiatives.
 
 
 &nbsp;
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design and implement AI, Machine Learning, Generative AI, and predictive analytics solutions that deliver measurable business value.
 </li>
 <li>
 Develop advanced analytics models, dashboards, and executive reporting frameworks to support strategic and operational decision-making.
 </li>
 <li>
 Analyze structured and unstructured data to identify trends, opportunities, risks, and performance improvement initiatives.
 </li>
 <li>
 Build, deploy, and optimize machine learning models for forecasting, planning, operational efficiency, and business insights.
 </li>
 <li>
 Partner with business stakeholders to identify AI and analytics opportunities and translate requirements into practical solutions.
 </li>
 <li>
 Support enterprise data governance, data quality, reporting standards, and AI governance frameworks.
 </li>
 <li>
 Drive digital transformation initiatives through intelligent automation, analytics, and emerging technologies.
 </li>
 <li>
 Collaborate with technology vendors and internal teams to deliver scalable, secure, and compliant AI and analytics solutions.
 </li>
 </ul>
 
 &nbsp;
 
 
 
 Requirements
 
 
 <ul>
 <li>
 Bachelor&rsquo;s Degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Statistics, Mathematics, Engineering, or a related field.
 </li>
 <li>
 6-8 years of experience in AI, Data Analytics, Business Intelligence, or Enterprise Data Management, including hands-on experience delivering AI and Machine Learning solutions.
 </li>
 <li>
 Strong expertise in Artificial Intelligence, Machine Learning, Predictive Analytics, Data Modelling, and Business Intelligence platforms such as Power BI or Tableau.
 </li>
 <li>
 Advanced proficiency in Python, SQL, data engineering, and analytics solution development.
 </li>
 <li>
 Experience developing executive dashboards, reporting frameworks, and enterprise-wide analytics solutions.
 </li>
 <li>
 Good understanding of data governance, AI governance, information security, and data privacy principles.
 </li>
 <li>
 Experience with ERP environments (SAP preferred) and digital transformation initiatives is advantageous.
 </li>
 <li>
 Relevant certifications in AI, Data Analytics, Cloud AI, Machine Learning, Power BI, or related technologies are highly desirable.
 </li>
 </ul>
 
 &nbsp;
 
 
 
 Join e7 Group and be part of a dynamic organization committed to excellence, innovation, and sustainable growth across diverse industries.
 
 
</div>

Senior Specialist - AI and Data Analytics

bankfab

<div><div>Job Description</div>
<div>
 JOB SUMMARY / INTRODUCTION
<ul><li>To lead the engineering, architecture, and run-state ownership of the bank's enterprise AI &amp; Agentic Platform, ensuring it operates as a reliable, secure, observable, and bank-grade production platform supporting agents and AI workloads across the Group.
</li><li>The role is the senior technical authority for platform engineering and architecture across the agentic runtime, model gateway, integration fabric, identity layer, and infrastructure backbone of the platform.
</li><li>It operates in a two-in-a-box model with the existing Platform Product Owner to provide concurrent technical ownership and organizational resilience for the platform, with shared accountability for platform availability, performance, cost, security posture, and architectural evolution.
</li>The role is deeply technical in nature, requiring hands-on engineering depth across distributed systems, agentic protocols, LLM infrastructure, identity and access management, and cloud-native platform engineering. 
<li>
 </li></ul>KEY RESPONSIBILITIES
 Key Accountabilities &mdash; Platform Architecture 
 
<ul><li>Own the end-to-end technical architecture of the AI &amp; Agentic Platform's five-layer stack: Action Gateway, Agent Kernel, Control Plane, Knowledge Foundation, and the Users and Channels layer.
</li><li>Architect and evolve the agentic runtime to natively support the emerging multi-protocol stack: Model Context Protocol (MCP) for agent-to-tool access, Agent-to-Agent (A2A) for inter-agent coordination and task delegation, Agent Communication Protocol (ACP) and equivalent emerging standards, ensuring the platform is interoperable with hyperscaler agent fabrics (Azure AI Foundry agents, AWS Bedrock Agents, Google ADK).
</li><li>Design the platform's agent kernel, including agent lifecycle management, planning and reasoning loops, memory architecture (short-term, long-term, episodic), state management, session affinity, scratchpad persistence, and execution chains.
</li><li>Architect the platform's knowledge foundation, including vector store selection and topology, hybrid retrieval (BM25, dense, graph), embeddings strategy, knowledge graph integration (FIBO, OWL, SHACL, SPARQL), context engineering, and grounding patterns.
</li><li>Design the platform's control plane, including policy-gated execution, Know Your Agent (KYA) enforcement at runtime, agent registries, tool registries, capability discovery, evaluation pipelines, and tracing and lineage at agent and tool granularity.
Key Accountabilities &mdash; Integrations &amp; Model Layer
</li><li>Architect and engineer the platform's LLM gateway and model abstraction layer, providing a unified interface across foundation model providers (Azure AI Foundry, AWS Bedrock, OpenAI, Anthropic, Google Vertex AI, Cohere) with intelligent routing, fallback, retries, prompt and response caching, semantic caching, rate limiting, token accounting, cost attribution, and tenant isolation.
</li><li>Design model serving patterns for managed APIs, dedicated capacity (PTUs / provisioned throughput), and self-hosted open-weight models on GPU infrastructure (vLLM, TGI, Triton, or equivalent), with appropriate trade-offs across cost, latency, sovereignty, and compliance.
</li><li>Lead the integration architecture between the AI Platform and the bank's core estate, including core banking, payments, treasury, credit and risk systems, the enterprise data platform (Azure, Cloudera, Databricks), enterprise APIs, ESB, event streaming (Kafka, Event Hubs), and the data product layer.
 
Design the action gateway as the bank's enforcement boundary for agentic action, including API mediation, contract enforcement, circuit breakers, idempotency guarantees, transactional safety, and audit-grade action logging.
</li><li>Engineer the platform's tool layer and MCP server estate, including tool packaging, versioning, capability advertisement, schema enforcement, and runtime tool discovery across Wholesale, Retail, and Group functions.
Key Accountabilities &mdash; Identity, Security &amp; Governance
</li><li>Architect and own the agent identity and workload identity model for the platform, including non-human identity (NHI) management, agent identity lifecycle, blended user-plus-agent identity for delegated actions, and the identity propagation chain across multi-agent flows.
 
Design the platform's authentication and authorization architecture, including OAuth 2.1 and OIDC flows for agent-to-tool and agent-to-API interactions, just-in-time credential issuance, short-lived token exchange, mTLS for agent-to-agent communication, and integration with the bank's enterprise IAM (Microsoft Entra ID, PAM, secrets management).
</li><li>Implement zero-trust principles across the agentic stack, including least-privilege scoping per agent and per task, real-time policy evaluation, behavioral posture checks, and continuous authorization rather than static service-account-style access.
</li><li>Engineer the platform's runtime governance controls, including KYA enforcement, prompt and output guardrails (PII, PHI, MNPI, prompt injection defense), sensitive action approval flows, and human-in-the-loop escalation patterns.
</li><li>Harden the platform to meet CBUAE, internal model risk, and Group governance requirements, including auditability, lineage, data residency, model risk controls, third-party model governance, and OWASP LLM Top 10 alignment.
</li><li>Key Accountabilities &mdash; Infrastructure &amp; Run-State
</li><li>Lead the platform's cloud and infrastructure architecture across Azure (primary) and AWS, including infrastructure as code (Terraform), networking (private endpoints, peering, egress control), Kubernetes (AKS) and container orchestration, secrets management, and CI/CD pipelines.
</li><li>Own platform Site Reliability Engineering (SRE), including SLO design, error budget management, observability (OpenTelemetry, traces, metrics, logs at agent and tool granularity), incident response, post-mortems, capacity planning, and cost governance for a growing fleet of agents and AI workloads in production.
 
Operate in genuine two-in-a-box with the existing Platform Product Owner, including shared on-call, shared roadmap ownership, and shared accountability for major architectural decisions, regulator conversations, and critical incidents.
</li><li>Drive engineering excellence across the platform team, including testing discipline (unit, integration, evaluation, red-teaming), documentation, infrastructure as code maturity, operational readiness reviews, and technical mentorship of platform engineers.
</li><li>Represent the platform in senior technical forums with Enterprise Architecture, Cyber, Model Risk, Internal Audit, and the Group CTTO's office on architecture and engineering matters.
</li><li>Engage with hyperscale, model provider, and framework vendor technical teams on platform-level integration, performance, sovereignty, and cost optimization.
REQUIREMENTS / QUALIFICATIONS
Technical Expertise
</li><li>Deep, current expertise in agentic AI architecture and the modern multi-protocol stack: Model Context Protocol (MCP), Agent-to-Agent (A2A), Agent Communication Protocol (ACP), and the engineering patterns required to build interoperable agentic systems on top of them at platform scale.
 
Strong hands-on knowledge of agent orchestration frameworks (LangGraph, Google ADK, LlamaIndex, Autogen, CrewAI, OpenAI Agents SDK, or equivalent), planning and reasoning loops, multi-agent coordination patterns, agent memory systems, and evaluation harnesses (RAGAS, OPIK, LangSmith, Promptfoo, or equivalent).
</li><li>Deep technical knowledge of LLM serving and inference architecture, including managed model APIs (Azure AI Foundry, AWS Bedrock, OpenAI, Anthropic, Google Vertex AI), provisioned throughput / PTUs, self-hosted open-weight models, GPU scheduling, vLLM / TGI / Triton, KV-cache management, batching strategies, and the cost-latency-quality trade-offs that drive model selection.
</li><li>Strong working expertise in LLM gateway and AI gateway architecture, including model routing, fallback and retry, prompt and semantic caching, rate limiting, tenant isolation, token accounting, and policy enforcement at the gateway boundary.
</li><li>Deep experience in retrieval and knowledge architecture, including vector databases (pgvector, Azure AI Search, Pinecone, Weaviate, Qdrant, or equivalent), hybrid retrieval, reranking, embeddings model selection, knowledge graphs (FIBO, RDF, OWL, SHACL, Neo4j, Apache Jena), and context engineering at scale.
 
Strong grounding in agent and workload identity, including non-human identity (NHI) governance, agent identity lifecycle, OAuth 2.1, OIDC, SPIFFE / SPIRE-style workload identity, mTLS, just-in-time credentialing, secret-less architectures, and integration with enterprise IAM (Microsoft Entra ID, Azure AD, PAM platforms).
</li><li>Deep proficiency in cloud-native platform engineering on Azure (preferred) and AWS, including Terraform, Kubernetes (AKS / EKS), Helm, service mesh (Istio, Linkerd), API gateways (APIM, Kong, Envoy), private networking, and policy-as-code (OPA, Azure Policy).
 
Strong programming proficiency in at least one of Python, Go, or Java, with active engagement in code reviews, design reviews, and platform-level engineering decisions.
</li><li>Strong Site Reliability Engineering background, including production on-call, incident leadership, post-mortem discipline, SLO and error-budget design, capacity planning, and observability tooling (Open Telemetry, Prometheus, Grafana, Datadog, or equivalent) tuned for non-deterministic AI workloads.
 
Working knowledge of integration patterns relevant to banking platforms, including event-driven architectures (Kafka, Event Hubs), API gateways, ESB, ISO 20022, payment rails, and core banking integration patterns.
</li><li>Strong grounding in security engineering for regulated industries, including OWASP LLM Top 10, prompt injection defence, model supply-chain security, secrets management, network segmentation, data residency, and audit logging.
 
Engineering Leadership &amp; Collaboration
</li><li>Demonstrated ability to operate effectively in a two-in-a-box model with another senior technical owner, including shared accountability, shared on-call, and shared decision-making.
</li><li>Track record of raising engineering standards across a platform team through standards, design reviews, documentation, and direct technical mentorship.
 
Strong written and verbal communication, with the ability to engage credibly with engineers, architects, risk and audit functions, hyperscaler and vendor technical teams, and senior business stakeholders.
 
Minimum Experience
</li><li>10+ years in software and platform engineering, with significant time spent at senior, staff, or principal engineering / architect level.
 
Demonstrated production ownership of at least one platform serving multiple internal or external consumers at enterprise scale, ideally including agentic or LLM workloads.
</li><li>Substantive experience in financial services, banking, or another comparably regulated industry.
 
Demonstrated SRE and on-call experience on a production platform with meaningful availability and operational requirements.
 
Track record of building, integrating, or operating LLM-based or agentic systems in production.
Minimum Qualifications
</li><li>Bachelor's degree in computer science, Software Engineering, Electrical Engineering, or a related technical discipline.
Preferred / Beneficial
</li><li>Master's degree (MSc / MTech / MEng) in Computer Science, Software Engineering, Distributed Systems, or a related discipline preferred.
</li><li>Relevant professional certifications in cloud engineering (Azure Solutions Architect Expert, Azure DevOps Engineer Expert, AWS DevOps Professional, AWS
</li><li>Solutions Architect Professional, Certified Kubernetes Administrator), security (CISSP, CCSP), or SRE considered an advantage.</li></ul></div></div>
 <div><div>Responsibilities</div></div><div></div>
 <div><div>Qualifications</div></div><div></div>
 <div><div>About Us</div>
<div><div>About Us: 
</div><div></div> 
<div>First Abu Dhabi Bank (FAB) is the largest bank in the UAE and one of the world's largest and safest financial institutions. We offer a comprehensive range of personal and private banking services, including credit cards, Islamic banking, investments, loans, and mortgages. Our commitment to excellence and innovation drives us to provide top-tier financial solutions to our clients. 
</div><div></div> 
<div>Life at FAB: 
</div><div></div> 
<div>Working at FAB means being part of a team of talented and passionate individuals with a shared vision to support the ambitions of our stakeholders to &quot;Grow Stronger.&quot; We embrace the needs of our customers across the globe with a sense of responsibility and confidence driven by extensive expertise that can only be delivered by an ambitious world-class organization 
</div><div></div> 
<div>Career Development: 
</div><div></div> 
<div>FAB offers unique career choices, a chance to innovate, craft solutions for the future, and express yourself in a performance-based culture that will unleash the best in you. Whether you are an experienced professional or just starting your career, FAB provides a range of learning and development initiatives to support all employees through training and skill development. 
</div><div></div> 
<div>Our Values: 
</div><div></div> 
<div>At FAB, we place our customers at the core of our activities, live our values each day in every way, celebrate achievements, and empower each other to deliver leading solutions. We have structured plans for the recruitment and career progression of Emirati talent to enable them to make a mark in the financial and banking sector both regionally and globaly that rewards your hard work and dedication. 
</div><div></div> 
<div>Join our team and be part of a journey to shape the future of banking.</div></div></div><div></div>

Senior Engineer, Platform Engineering and Architecture

DICETEK LLC

<div>JOB PURPOSE:
We are looking for an experienced AI Architect responsible for architecting enterprise-wide Generative AI and Agentic AI capabilities across banking systems. The role will define target architecture, integration patterns, standards, reference implementations and reusable building blocks for full-fledged AI chat assistants, autonomous agents and multi-agent workflows.
The AI Architect will lead end-to-end architecture for agentic retail banking journeys such as payments, transfers, servicing, self-service fulfilment and customer assistance, ensuring secure integration with enterprise APIs, middleware, core banking platforms and customer-facing channels across web and mobile.
This role requires deep hands-on AI engineering capability, strong banking domain understanding, practical delivery experience with multiple production-grade banking agents, and the ability to collaborate with product, engineering, infrastructure, cybersecurity, data, governance and enterprise architecture teams to present and align designs through ARB. 
QUALIFICATIONS &amp; EXPERIENCE:
Minimum Qualification<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, Data Science or a related discipline.</li><li>Relevant certifications in cloud architecture, AI engineering, security architecture, enterprise architecture or machine learning are preferred.</li></ul> 
Minimum Experience<ul><li>Senior technology professional with around 12+ years of experience across software engineering, architecture, cloud/platform engineering and enterprise solution delivery.</li><li>Minimum 4+ years of hands-on AI engineering or AI architecture experience, including Generative AI, LLM applications and Agentic AI solutions.</li><li>Proven experience architecting and delivering multiple banking agents or full-fledged banking chat assistant capabilities integrated with enterprise systems.</li><li>Strong understanding of banking systems, retail banking journeys, payments, transfers, servicing, customer self-service, operational controls and regulatory/security considerations.</li><li>Full AI Engineer capability including Python, API integration, microservices, event-driven design, RAG implementation, model/agent evaluation and cloud-native deployment practices.</li><li>Hands-on experience with agent frameworks and orchestration platforms such as Microsoft Semantic Kernel, AutoGen, LangChain, LangGraph and similar frameworks.</li><li>Experience architecting MCP servers, tool integration layers, agent-to-agent communication, UI integration patterns and agent interoperability protocols such as MCP, A2A and A2UI.</li><li>Strong experience with Azure AI services, Azure OpenAI Service, AWS AI services, Amazon Bedrock and related model deployment/management capabilities.</li><li>Experience designing secure AI systems with zero trust principles, identity and access controls, data protection, secure API design, PII redaction and privacy-by-design controls.</li><li>Experience presenting solution architecture, trade-off analysis, ADRs and architecture recommendations to ARB or equivalent architecture governance forums.</li><li>Experience recommending infrastructure architecture for AI platforms including compute, Kubernetes, serverless, vector databases, observability, monitoring, data pipelines and connectivity.</li><li>Strong capability to collaborate with engineering, product, cybersecurity, infrastructure, operations, data, compliance and enterprise architecture teams.</li></ul> 
Key Technical Skills<ul><li>Enterprise Agentic AI architecture, multi-agent systems, autonomous workflows, human-in-the-loop design and full-fledged chat assistant architecture.</li><li>LLMs, prompt engineering, context engineering, memory design, tool/function calling, agent orchestration, model/agent evaluation and cost/latency optimization.</li><li>RAG architecture, semantic indexing, embeddings, vector databases, retrieval optimization, reranking, grounding, answer relevancy and explainability patterns.</li><li>MCP server architecture, tool registries, multi-tool integration, A2A, A2UI, agent interoperability protocols and AI ecosystem design.</li><li>Azure AI, Azure OpenAI, AWS AI services, Amazon Bedrock, Kubernetes, serverless, microservices, APIs, event-driven architecture and observability.</li><li>Security architecture for AI systems including zero trust, PII redaction, data masking, privacy controls, guardrails, secure logging and auditability.</li></ul> 
Behavioural / Leadership Skills<ul><li>Strategic architecture thinking with the ability to define enterprise standards, influence platform direction and simplify complex technical decisions.</li><li>Strong stakeholder communication with the ability to present architecture options, risks, trade-offs and recommendations to senior leadership and ARB forums.</li><li>Collaborative leadership style with the ability to work across business, product, engineering, cybersecurity, data and infrastructure teams.</li><li>Hands-on problem-solving mindset, pragmatic decision making, ownership, mentoring capability and commitment to high-quality secure delivery.</li></ul> 
Technical Competencies<ul><li>Enterprise Agentic AI architecture and banking-grade AI ecosystem design.</li><li>Retail banking agent architecture for payments, transfers, servicing and self-service workflows.</li><li>RAG, memory, context engineering, evaluation, tool orchestration and MCP server architecture.</li><li>AI security architecture, zero trust, PII redaction, guardrails, auditability and governance.</li><li>Azure and AWS AI services, cloud-native infrastructure, Kubernetes, serverless and observability for agent platforms.</li><li>Architecture documentation, ADR creation, ARB presentation and cross-team design governance.</li></ul> 
Skills: AI Architecture , LLMs , Azure AI</div>

AI Architect – Enterprise Agentic AI Architecture

Masdar

<div>Company Description 
Established in 2006, Masdar (Abu Dhabi Future Energy Company) is a global clean energy leader, transforming how the world produces and consumes energy through bold innovation and commercial excellence.
Masdar is a clean energy investor, developer and operator, advancing renewable energy projects across key markets and technologies, with a global project portfolio capacity to date of over 65 gigawatts (GW).
Jointly owned by TAQA, ADNOC and Mubadala, Masdar is driving the scale-up of renewables worldwide, targeting a portfolio capacity of 100GW by 2030. 
Job Description 
To support the development of analytics, AI, and data products while building foundational capabilities, as part of Masdar&rsquo;s national-talent development within the AI Products &amp; Analytics Technology CoE.
Key Accountabilities :<ul><li>
Perform data preparation, cleaning, and analysis.</li><li>
Support the development of analytical models and data pipelines across key use cases</li><li>
Assist in implementing machine learning, statistical, and optimization models under guidance from senior team members</li><li>
Perform data cleaning, preprocessing, and exploratory data analysis (EDA)</li><li>
Translate analytical outputs into clear insights, visualizations, and reports</li><li>
Support the delivery of data-driven recommendations to inform operational and strategic decisions</li><li>
Contribute to dashboards and tools that enhance visibility into performance and forecasts</li><li>
Develop dashboards and reports on the CoE&rsquo;s BI platforms.</li><li>
Support AI model development, testing, and documentation.</li><li>
Work closely with the Senior Decision Scientist to Build and refine models, Validate results and ensure quality outputs, and Understand business context and decision frameworks</li><li>
Participate in code reviews, model reviews, and knowledge-sharing sessions</li><li>
Ensure high standards of data integrity, quality checks, and documentation</li><li>
Work with structured and unstructured datasets from multiple sources</li><li>
Support the maintenance of reproducible and well-documented codebases</li><li>
Build foundational skills in data science, AI, and platform tools through structured development.</li><li>
Apply best practices in coding, modeling, and analytics inspired by industry-leading organizations</li><li>
Engage with stakeholders across operations, digital, and strategy teams to understand data needs</li><li>
Support the translation of business questions into analytical tasks</li><li>
Communicate findings in a clear and structured manner appropriate for different audiences</li></ul> 

Qualifications 
Preferred Qualifications:<ul><li>
Bachelor&rsquo;s degree in Computer Science, Data Science, Engineering, or a related field; UAE National (National Talent programme). Strong foundation in statistics, linear algebra, and data analysis.
</li></ul>Preferred Experience:<ul><li>
1&ndash;3 years of experience in data science, analytics, or related fields (internships included)</li><li>
Job-Exposure to energy, utilities, or financial analytics is advantageous but not mandatory</li><li>
Demonstrated experience working on data-driven projects (academic or professional)</li></ul>
Technical Skills:<ul><li>
Proficiency in Python, SQL, or similar programming languages</li><li>
Familiarity with:</li><li>
Data analysis libraries (e.g., Pandas, NumPy)</li><li>
Visualization tools (e.g., Power BI, Tableau, Matplotlib)</li><li>
Basic machine learning concepts and frameworks</li><li>
Understanding of data pipelines and data wrangling techniques</li><li>
Exposure to cloud platforms or big-data tools is a plus</li></ul>
Behavioral Competencies:<ul><li>
Strong analytical thinking and problem-solving skills</li><li>
Curiosity and eagerness to learn and grow in a fast-paced environment</li><li>
Ability to take direction, absorb feedback, and continuously improve</li><li>
Good communication skills with the ability to explain findings clearly</li><li>
Collaborative mindset and strong attention to detail</li></ul> 
Role is to be based in Abu Dhabi, UAE. 
Additional Information<div></div> 
As part of the application process, we will collect, store and process personal information about you.
Masdar will use your personal information in accordance with our Candidate Privacy Notice, which provides details on the purposes for which your data is processed.</div>

Data Scientist

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