enterprise architect

Accenture Middle East

<div>
 
 Location: Dubai/Abu Dhabi, UAE
 
 
 
 
 About Accenture
 
 
 
 Accenture is a leading global professional services company that helps the world&rsquo;s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services&mdash;creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 799,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world&rsquo;s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy &amp; Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360&deg; value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360&deg; value we create for our clients, each other, our shareholders, partners and communities. Visit us at
 
 www.accenture.com
 
 .
 
 
 
 Accenture Strategy
 
 
 &amp; Consulting
 
 
 
 In today&rsquo;s world, business leaders want to rapidly and confidently reinvent to increase resilience, mitigate risk, and grow with sustainable value. That&rsquo;s where Accenture Strategy &amp; Consulting comes in. We bring together strategic visionaries, industry experts, practitioners from across every enterprise function, business intelligence professionals, change specialists, data and AI authorities, and many other specialized skills to co-create each client&rsquo;s unique path to reinvention. You will be a trusted partner to business leaders, working with a diverse team of experts to deliver successful tech-enabled transformation and new kinds of value for your clients.
 
 
 
 Key Responsibilities
 
 
 
 
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 Drive rigorous and structured approach to identifying and solving complex technology business problems that leads to strategic insights
 
 </li>
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 Identify/prioritize value creation opportunities at the intersection of business and technology based on assessment activities and an understanding of high-level visions, performance gaps, and needs
 
 </li>
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 Lead independently small engagements or stream of work end-to-end across all delivery components: client satisfaction, value delivered, teams management, financials, etc.
 
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 Identify and nurture pull-through business opportunities, support business development effort with client and Accenture teams until successful sale closure
 
 </li>
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 Collaborate with clients and within Accenture to align their business and technology priorities
 
 </li>
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 Develop content knowledge and share through pro-active involvement in technology strategy operations and community of practices
 
 </li>
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 Lead the creation of well-articulated thought leadership assets that present innovative insights, knowledge, guidance and recommendations on a specific market-relevant technology strategy domain
 
 </li>
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 Interaction with senior management at a client and/or Accenture to steer recommendations and obtain buy-in on matters that may require alternate approach
 
 
 
 </li>
 
 Key Skills
 
 
 
 
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 Strong data-driven consulting with focus on business and technology value architecting and realization
 
 </li>
 <li>
 Ability to act independently to determine methods and procedures on assignments
 
 </li>
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 Management of team efforts at a client or within Accenture
 
 </li>
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 Ability to pull-through business opportunities
 
 </li>
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 Experience and understanding of core technology strategy offerings &ndash; IT &amp; Digital technology strategy, enterprise architecture, operating model, data &amp; analytics, cloud
 
 </li>
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 Experience in technology advisory and/or implementation
 
 </li>
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 Ability to operate cross industry, with preferred experience in Banking, Telcos, Oil&amp;Gas, and/or Government
 
 </li>
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 Pro-actively acquired business knowledge beyond technical role or via business school i.e. MBA
 
 
 
 </li>
 
 External Hire Archetype
 
 
 
 
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 Minimum 4-8 years of total work experience - at least 3 years in IT/Digital technology strategy
 
 </li>
 <li>
 Proven and relevant past consulting experience; alternatively strong in-house IT &amp; Digital strategy / enterprise architecture division / advanced startup / pre-sales roles (and demonstration of intrinsic consulting skills)
 
 </li>
 <li>
 Arabic speaking must and fluent English
 
 
 
 </li>
 
 Why join us?
 
 
 
 
 <li>
 We offer a transparent, fast paced approach career progression, with a focus on your strengths and continuous coaching from senior colleagues
 
 </li>
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 You will benefit from working alongside Accenture experts who are solving some of the biggest industry challenges with innovative thinking and pioneering tools
 
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 Flexible work arrangements and a range of benefits including competitive rewards
 
 </li>
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 You will have access to state-of-the-art technology that will give you the opportunity to deepen your existing skills even as you help create the latest business trends
 
 </li>
 <li>
 You will also have opportunities to make a difference to the communities in which we work and live
 
 
 
 </li>
 
 Next Steps
 
 
 
 If this sounds like the ideal role, career and company for you, click below to apply.
 
 
 To learn more about life @AccentureMiddleEast, follow us on social media and keep up with our latest news.
 
 
 Accenture Middle East: LinkedIn, Instagram, Facebook, Twitter, YouTube
 
 
</div>

Technology Strategy/Enterprise Architect Consultant

Unity Infotech

<div>
 
 
 Role: Senior Solutions Architect / Engineer
 
 
 
 
 Experience:
 
 7&ndash;10 Years
 
 
 
 Location:
 
 UAE
 
 
 
 
 
 The Senior Solutions Architect / Engineer will be responsible for the design, implementation,
 
 
 integration, and production support of Wealth Management, Brokerage, and Investment
 
 
 platforms. The role requires deep techno-functional expertise across wealth asset classes, trading
 
 
 systems, consumer banking integrations, and modern cloud-native architectures, with strong
 
 
 ownership of production stability, scalability, and regulatory compliance.
 
 
 The position demands hands-on technical leadership, proactive system resilience improvements, and
 
 
 24/7 on-call production support in a highly regulated financial environment.
 
 
 
 
 
 
 Required Skills &amp; Experience
 
 
 
 
 Mandatory
 
 
 
 &bull;7&ndash;10 years of experience in
 
 financial services technology
 
 , with strong focus on
 
 wealth
 
 
 
 
 management and brokerage platforms
 
 
 
 &bull;Hands-on experience in
 
 production support and system operations
 
 
 
 &bull;Strong analytical, troubleshooting, and problem-solving skills
 
 
 &bull;Excellent communication and stakeholder management capabilities
 
 
 &bull;Ability to work in fast-paced, regulated environments
 
 
 
 Desirable
 
 
 
 &bull;Experience working in
 
 UAE or GCC banking environments
 
 
 
 &bull;Exposure to
 
 digital assets Trading Platform Implementation
 
 
 
 &bull;Exposure to
 
 digital assets
 
 Custody Platform Implementation
 
 
 &bull;Cloud certifications (AWS / Azure)
 
</div>

Solution Architect- Wealth Management

Xebia

<div>
 
 We are seeking a
 
 Databricks Architect
 
 with deep expertise in
 
 Azure Data Platform, Data Modelling, and Medallion (Lakehouse) Architecture
 
 . The ideal candidate will design and implement scalable, high-performance data solutions using
 
 Databricks, Delta Lake, and modern data engineering practices
 
 , enabling enterprise-wide analytics and business intelligence.
 
 
 
 
 
 
 Location:
 
 Abu Dhabi
 
 
 
 Experience:
 
 10&ndash;15+ Years
 
 
 
 Email
 
 : vijay.kajla@xebia.com
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 Medallion Architecture &amp; Lakehouse Design
 
 
 <ul>
 <li>
 Design and implement
 
 Medallion Architecture (Bronze, Silver, Gold layers)
 
 on
 
 Azure Databricks
 
 </li>
 <li>
 Define data flow standards across ingestion, cleansing, transformation, and consumption layers
 </li>
 <li>
 Ensure
 
 data quality, lineage, and governance
 
 across all layers
 </li>
 <li>
 Optimize storage and compute using
 
 Delta Lake features (ACID transactions, time travel, schema evolution)
 
 </li>
 </ul>
 
 
 Architecture &amp; Strategy
 
 
 <ul>
 <li>
 Architect
 
 end-to-end Azure data platforms
 
 using:
 </li>
 <li>
 Azure Databricks
 </li>
 <li>
 ADLS Gen2
 </li>
 <li>
 Azure Data Factory
 </li>
 <li>
 Azure Synapse
 </li>
 <li>
 Define
 
 data platform standards, best practices, and reusable frameworks
 
 </li>
 <li>
 Lead
 
 data modernization initiatives
 
 (on-prem to cloud, legacy to lakehouse)
 </li>
 </ul>
 
 
 Data Engineering Leadership
 
 
 <ul>
 <li>
 Build scalable pipelines using
 
 PySpark, Spark SQL, and Databricks workflows
 
 </li>
 <li>
 Implement
 
 batch + real-time ingestion patterns
 
 </li>
 <li>
 Drive
 
 performance tuning and cost optimization
 
 </li>
 <li>
 Mentor teams on
 
 Spark optimization, partitioning, and job orchestration
 
 </li>
 </ul>
 
 
 Data Modelling
 
 
 <ul>
 <li>
 Design
 
 enterprise-grade data models
 
 :
 </li>
 <li>
 Dimensional (Star/Snowflake)
 </li>
 <li>
 Normalized and Data Vault (nice to have)
 </li>
 <li>
 Align data models with
 
 Gold layer consumption use-cases (BI/Reporting)
 
 </li>
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 Translate business needs into
 
 scalable analytical datasets
 
 </li>
 </ul>
 
 
 Integration &amp; Consumption
 
 
 <ul>
 <li>
 Build ingestion pipelines using:
 </li>
 <li>
 
 ADF, Event Hub, Kafka, APIs
 
 </li>
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 Enable reporting via:
 </li>
 <li>
 
 Power BI, Tableau, or similar BI tools
 
 </li>
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 Ensure seamless consumption from
 
 Gold datasets
 
 </li>
 </ul>
 
 
 Stakeholder Engagement
 
 
 <ul>
 <li>
 Act as a
 
 data architecture SME
 
 in client discussions
 </li>
 <li>
 Drive solutioning, architecture reviews, and governance forums
 </li>
 <li>
 Collaborate with business teams for
 
 data-driven decision making
 
 </li>
 </ul>
 
 
 Required Skills
 
 
 
 
 Core
 
 
 <ul>
 <li>
 Strong hands-on experience with
 
 Azure Databricks &amp; Delta Lake
 
 </li>
 <li>
 Proven expertise in
 
 Medallion Architecture implementation
 
 </li>
 <li>
 Advanced
 
 PySpark and Spark SQL
 
 </li>
 <li>
 Experience with
 
 ADF, ADLS Gen2, Synapse
 
 </li>
 </ul>
 
 
 Data Modelling
 
 
 <ul>
 <li>
 Strong experience in:
 </li>
 <li>
 
 Dimensional modelling (must-have)
 
 </li>
 <li>
 Data modelling aligned to
 
 Gold layer analytics
 
 </li>
 <li>
 Understanding of
 
 data quality and governance frameworks
 
 </li>
 </ul>
 
 
 Nice-to-Have
 
 
 <ul>
 <li>
 Real-time processing (
 
 Kafka / Spark Streaming
 
 )
 </li>
 <li>
 Azure Purview or data governance tools
 </li>
 <li>
 ML pipelines on Databricks
 </li>
 <li>
 Domain: Airlines / BFSI / Retail
 </li>
 </ul>
 
 
 Leadership Skills
 
 
 <ul>
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 Strong architectural thinking
 </li>
 <li>
 Client-facing experience
 </li>
 <li>
 Ability to lead and scale engineering teams
 </li>
 <li>
 Excellent communication and stakeholder management
 </li>
 </ul>
 
 
 
 
 We are an Equal Opportunity Employer committed to fostering a diverse, inclusive, and respectful workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We believe diversity drives innovation and success, and we welcome individuals from all backgrounds to join our team.
 
</div>

Data Architect

ENEC Operations

<div>
 
 The Data and AI Engineering Expert is a senior hands-on technical authority responsible for the design, development, and operationalization of enterprise data and AI platforms across ENEC. This role leads the engineering delivery of scalable, secure, and compliant data pipelines, AI/ML solutions, and analytics platforms leveraging technologies such as Databricks (Delta Lake, Unity Catalog, MLflow, Delta Live Tables), Microsoft Azure (Azure Data Factory, Azure ML, Microsoft Fabric, Azure AI Foundry, Copilot Studio), Collibra (Data Governance &amp; Data Quality), Power BI, and OT/industrial data systems including PI System, SCADA, and DCS.
 
 
 
 
 
 The Expert applies deep engineering expertise to architect and deliver production-grade solutions, ensures data governance and quality standards are upheld, and drives the adoption of AI and analytics capabilities that directly support ENEC's mission of safe, innovative, and efficient nuclear energy generation. This role acts as a principal technical contributor and mentor, enabling operational excellence and digital transformation at scale.
 
 
 Activity: Data Engineering Architecture &amp; Platform Development
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design, build, and maintain scalable, secure, and high-performance data platforms including Lakehouse architectures using Databricks Delta Lake, Unity Catalog, and Delta Live Tables (DLT).
 
 
 &bull; Develop and operationalize robust data pipelines, ETL/ELT workflows, and integration frameworks using Azure Data Factory, Databricks Workflows, and related orchestration tools.
 
 
 &bull; Architect and implement data models, semantic layers, and data products that serve enterprise analytics, AI, and reporting needs.
 
 
 &bull; Ensure seamless integration of OT and industrial data sources &mdash; including PI System, SCADA, and DCS &mdash; into enterprise data platforms.
 
 
 &bull; Design and implement APIs, data contracts, and integration frameworks to enable enterprise-wide data consumption.
 
 
 &bull; Ensure platform scalability, resilience, high availability, and disaster recovery capabilities in compliance with nuclear and regulatory requirements.
 
 
 &bull; Apply and enforce data standards, naming conventions, and metadata management practices across all data assets using Collibra and Unity Catalog.
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design, develop, and deploy production-grade machine learning, deep learning, and generative AI models using Azure ML, MLflow, and Databricks ML.
 
 
 &bull; Engineer end-to-end MLOps pipelines covering model training, versioning, validation, deployment, monitoring, and retraining &mdash; ensuring reliability and reproducibility.
 
 
 &bull; Build and operationalize AI-powered solutions including predictive analytics, anomaly detection, natural language processing (NLP), and GenAI/LLM-based applications using Azure AI Foundry and Copilot Studio.
 
 
 &bull; Develop BI and semantic models in Microsoft Fabric and Power BI, enabling self-service analytics and executive reporting across the organization.
 
 
 &bull; Apply Responsible AI principles and governance frameworks to all AI and ML solutions, ensuring explainability, fairness, and compliance.
 
 
 &bull; Conduct rigorous model evaluation, performance benchmarking, and validation to ensure solutions meet accuracy, reliability, and safety standards.
 
 
 &bull; Contribute to the continuous improvement of AI engineering standards, patterns, and reusable components across the enterprise.
 
 
 Activity: Advanced Subject Matter Knowledge
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Demonstrates deep, hands-on expertise in enterprise data engineering, AI/ML platform development, and cloud-native architectures within highly regulated environments.
 
 
 &bull; Maintains current knowledge of global trends in data engineering, MLOps, GenAI, cloud technologies (Azure, hybrid, on-premise), and nuclear industry compliance requirements.
 
 
 &bull; Understands the full lifecycle of data and AI platforms including design, development, testing, deployment, monitoring, and decommissioning.
 
 
 &bull; Applies comprehensive knowledge of data governance frameworks (Collibra, Unity Catalog), master data management, data quality, and lineage management.
 
 
 &bull; Possesses strong awareness of OT/IT convergence, industrial data systems (PI System, SCADA, DCS), and their integration into enterprise analytics environments.
 
 
 &bull; Maintains expert-level proficiency in programming languages and frameworks including Python, SQL, Spark, and relevant AI/ML libraries.
 
 
 Activity: Complex Problem Solving &amp; Innovation
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Tackles complex, ambiguous engineering challenges in data platform architecture, AI model development, and system integration &mdash; delivering innovative, compliant, and production-ready solutions.
 
 
 &bull; Leads root cause analysis and corrective/preventive actions for platform incidents, data quality failures, model degradation, and system disruptions.
 
 
 &bull; Develops and implements robust engineering solutions to address performance bottlenecks, scalability constraints, and integration challenges.
 
 
 &bull; Navigates conflicting technical requirements, evolving regulatory standards, and stakeholder needs to deliver optimal engineering outcomes.
 
 
 &bull; Drives continuous improvement by benchmarking against global engineering best practices, evaluating emerging technologies, and implementing lessons learned.
 
 
 &bull; Leads proof-of-concept and pilot initiatives to evaluate new data and AI technologies and engineering approaches
 
 
 
 
 
 Activity: Applied Skills &amp; Professional Know-How
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Expertly engineers, deploys, and operates scalable, secure, and compliant data and AI platforms across Databricks, Azure, and OT environments.
 
 
 &bull; Applies hands-on proficiency in building data pipelines, ML models, GenAI solutions, BI semantic models, and governance frameworks in production environments.
 
 
 &bull; Mentors and develops junior and mid-level data engineers, data scientists, and analytics engineers &mdash; building future-ready technical capabilities.
 
 
 &bull; Leads technical design reviews, code reviews, and architecture assessments to uphold engineering quality and best practices.
 
 
 &bull; Effectively translates complex technical concepts into clear, actionable insights for both technical and non-technical stakeholders.
 
 
 &bull; Documents solutions, engineering patterns, and technical standards to build institutional knowledge and enable knowledge transfer.
 
 
 Activity: Security, Governance &amp; Compliance
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design and enforce data security, access control, and privacy frameworks across all data and AI platforms using Unity Catalog, Collibra, and Azure security controls.
 
 
 &bull; Ensure all data engineering and AI solutions comply with national and international nuclear regulations, FANR requirements, and Responsible AI principles.
 
 
 &bull; Maintain comprehensive data lineage, audit trails, and documentation to support regulatory, audit, and governance requirements.
 
 
 &bull; Implement and enforce data quality frameworks and data governance policies using Collibra Data Quality and Unity Catalog.
 
 
 &bull; Conduct regular platform security assessments, data quality audits, and compliance reviews.
 
 
 &bull; Oversee risk management, audit readiness, and the implementation of robust technical controls for all platform operations.
 
 
 
 
 
 
 
 
 
 Minimum
 
 
 
 &bull; Bachelor&rsquo;s degree in computer science, Information Technology, Data Management, Engineering, or related discipline.
 
 
 &bull; Minimum 12+ years' hands-on experience in enterprise data engineering, AI/ML platform development, and cloud-native architectures, including production deployment and operations.
 
 
 &bull; Experience embedding governance within modern data platforms (preferably Databricks) and integrating SAP/Oracle ERP domains.
 
 
 
 
 
 
 
 
 
 Preferred
 
 
 
 
 
 
 &bull; Master&rsquo;s degree in a relevant field.
 
 
 &bull; Experience in energy, utilities, nuclear, financial services, government, or other highly regulated sectors.
 
 
 &bull; Demonstrated AI governance experience (provenance, bias monitoring, model data requirements) in data bricks or similar AI/analytics platforms exposure.
 
 
 &bull; Demonstrated experience leading large-scale data and AI engineering programs
 
 
 
 
 
 
 
 
 
 Certification -
 
 
 
 
 
 
 Multiple cloud and AI certifications. Microsoft Fabric, Azure AI Foundry, or Databricks Unity Catalog specialty certifications. Industry publications or contributions in data engineering or AI.
 
 
 
 
 
 Relevant certifications in one or more of: Databricks (Data Engineer Associate/Professional, ML Professional), Microsoft Azure (Data Engineer, AI Engineer, Solutions Architect), MLOps, or Data Governance (Collibra).
 
</div>

Data and AI Engineering Expert

Contango

<div>Contract duration: 6 months (with a potential extension) 
Engagement Type: Full-time 
Start date: July 2026 
Location: Abu Dhabi (on-site)
Role Overview
We are seeking an experienced AI Architect to define how we design, secure, and scale AI across the organization. You&rsquo;ll translate business strategy into reference architectures, platform decisions, and guardrails that engineering teams execute against &mdash; balancing capability, cost, risk, and time-to-value.
Where AI Engineers ship features, you&rsquo;ll shape the platform: model strategy, the data and retrieval foundation, the LLMOps backbone, the security posture, and the governance model. Increasingly, that means architecting agentic systems, multi-model routing, and responsible AI controls that comply with regulations like the EU AI Act. 
Key Responsibilities<ul><li>
Define AI strategy and reference architectures for generative AI, agentic systems, RAG, and predictive ML.</li><li>
Set model strategy: build-vs-buy, open-weight vs. hosted, multi-model routing, and a framework for evaluating new models as they ship.</li><li>
Architect the data and retrieval foundation &mdash; lakehouse, feature stores, vector stores, and lineage &mdash; that AI systems depend on.</li><li>
Design the LLMOps/MLOps platform: experiment tracking, model and prompt registries, automated eval gates, and observability.</li><li>
Lead AI security: threat modeling for prompt injection and data exfiltration, and OWASP LLM Top 10 mitigations.</li><li>
Own responsible AI and governance &mdash; risk classification, human oversight, auditability, and alignment with the EU AI Act, NIST AI RMF, and ISO/IEC 42001.</li><li>
Establish FinOps for AI: cost models, token budgeting, and unit economics per use case.</li><li>
Provide technical leadership, review designs, mentor engineers, and align stakeholders from engineering to the executive team. 
 
Candidate Requirements</li></ul><ul><li>
Demonstrated experience delivering AI solutions in an enterprise or client-facing/consulting environment.</li><li>
Prior experience at management consulting firms and/or Big Tech is an advantage.</li><li>
Bachelor's or Master&rsquo;s degree in Computer Science, Engineering, Information Technology, or a related field.</li><li>
8+ years in software/data engineering, with 3+ years architecting AI/ML or large-scale data systems.</li><li>
A track record of designing and delivering production AI systems end-to-end, ideally including GenAI/LLM workloads.</li><li>
Deep understanding of LLM and ML system design &mdash; RAG, agents, fine-tuning trade-offs, evaluation, serving, and the full MLOps/LLMOps lifecycle.</li><li>
Strong cloud architecture skills (Azure, AWS, or GCP) plus a modern data platform (Databricks or Snowflake).</li><li>
Expertise in AI security, responsible AI, and data governance, with awareness of relevant regulations.</li><li>
Excellent communication &mdash; able to influence both engineers and executives.</li><li>
Hands-on enough to prototype, review code, and earn engineering teams&rsquo; trust. 
Nice to have:
</li><li>Architecting AI for regulated or sovereign environments (finance, healthcare, government, GCC/UAE).</li><li>
Enterprise architecture frameworks (TOGAF) and well-architected reviews.</li><li>
Defining golden-path tooling for internal AI development.</li><li>
Running structured vendor PoCs and bake-offs.</li></ul>
Tools &amp; Technologies You&rsquo;ll Work With:<ul><li>
Patterns: RAG, agentic/multi-agent, event-driven, lakehouse/medallion; reusable blueprints.</li><li>
Model strategy: multi-model routing and gateways (LiteLLM, Portkey); Claude, GPT, Gemini, Llama, Mistral.</li><li>
Platforms: Azure AI Foundry, AWS Bedrock, Vertex AI, Databricks Mosaic AI.</li><li>
Data foundation: Delta Lake/Databricks, Snowflake, Unity Catalog, vector stores, knowledge graphs.</li><li>
LLMOps/MLOps: MLflow, LangSmith/Langfuse, model and prompt registries, eval-in-CI.</li><li>
Security &amp; governance: OWASP LLM Top 10, NIST AI RMF, ISO/IEC 42001, EU AI Act, RBAC/ABAC, secrets management.</li><li>
Infra &amp; observability: Kubernetes, Terraform/OpenTofu, OpenTelemetry; token/cost dashboards.</li></ul></div>

AI Architect (6 months contract)

Luxoft

<div><div><h5 class="jobSectionHeader">Project description
</h5>The Principal Full-Stack Architect (.NET &amp; Cloud) is a senior technical leader responsible for defining and driving the architecture of enterprise-scale applications across cloud, backend, frontend, data, DevOps, and AI-enabled solutions. The role combines strategic technology leadership with hands-on technical expertise, ensuring that solutions are scalable, secure, maintainable, and aligned with business objectives
</div><div><h5 class="jobSectionHeader">Responsibilities</h5>
<div><div>Drive the full SDLC for Azure solutions: planning, requirement definition, development, testing, and quality assurance.
</div><div>Develop, enhance, and integrate modules within core applications used by front-office investment teams.
</div><div>Design and build containerized applications (Docker, Kubernetes/AKS) and cloud-native data stores (Mongo, SQL).
</div><div>Develop RESTful APIs, microservices, and event-driven systems (Service Bus, Event Hubs) with strict secure-integration standards (OAuth2/OIDC, managed identities).
</div><div>Build responsive, cloud-connected front-end interfaces (React/TypeScript; real-time via SignalR).
</div><div>Design and deliver AI-enabled capabilities: document intelligence, retrieval/search (AI Search), and Azure OpenAI-based workloads over structured and unstructured data.
</div><div>Configure, maintain, and optimize CI/CD pipelines and infrastructure-as-code (Bicep/ARM, Terraform); enable self-service engineering capabilities.
</div><div>Implement large-scale data processing and advanced analytics solutions in collaboration with architecture and data teams.
</div><div>Own incident management: troubleshooting, root cause analysis, and preventive measures.
</div><div>Partner directly with senior IT and business stakeholders; own the platform narrative, adoption strategy, and delivery roadmap.
</div><div>Mentor cross-functional teams on cloud-native and AI best practices
</div></div></div><div><h5 class="jobSectionHeader">Skills</h5>
Must have
<div><div>Must have:
</div><div>10+ years overall IT experience with a proven track record of architecting and delivering scalable cloud solutions through all SDLC phases.
</div><div>10+ years of .NET (C#) development within service-oriented and microservices architectures, including: ASP.NET Core / Web API, Entity Framework Core, async and concurrency patterns, and hands-on migration from .NET Framework to .NET 6/
</div><div>Production code on a current LTS version is expected; legacy-only (.NET Framework, WebForms) profiles do not qualify.
</div><div>7+ years hands-on Microsoft Azure: App Services, Functions, Logic Apps, AKS/Container Apps, APIM, Service Bus/Event Hubs, AI Search, AI Services/Azure OpenAI, Storage, Key Vault, Application Insights, Monitor. Skills:
</div><div>Demonstrated architecture ownership: solution/application architecture defined and delivered end-to-end at enterprise scale, including presenting architectural strategy to senior leadership. Candidates with purely implementation-level experience will not be considered.
</div><div>5+ years containerization and orchestration (Docker, Kubernetes/AKS) in production.
</div><div>5+ years Azure DevOps and CI/CD, including infrastructure-as-code (Bicep/ARM mandatory; Terraform preferred).
</div><div>Practical delivery of AI/GenAI workloads on Azure (Azure OpenAI, AI Search, document intelligence, or equivalent) &mdash; in production, within the last 24 months. Proof-of-concept-only or pre-2024 experience does not qualify.
</div><div>Deep database expertise: NoSQL (Mongo) and relational SQL, including data access patterns for AI use cases.
</div><div>Expertise in designing and consuming secure REST APIs; strong understanding of network architecture and authentication protocols (OAuth2/OIDC, managed identities).
</div><div>Modern front-end delivery: React/TypeScript with real-time capabilities (SignalR).
</div><div>Experience in regulated environments (financial services / investment management strongly preferred). Required certifications:
</div><div>Microsoft Certified: Azure Solutions Architect Expert: required. Applications without it are not shortlisted.
</div><div>Plus at least one of: Azure DevOps Engineer Expert or Azure AI Engineer Associate.
</div></div>Nice to have
<div><div>AWS and/or GCP exposure (multi-cloud evaluation experience)
</div><div>Terraform in production
</div><div>Python
</div><div>Databricks (recent, Unity Catalog-era experience) or comparable data/AI platforms; Palantir exposure
</div><div>Azure Security Engineer Associate
</div><div>Experience establishing self-service platforms for citizen developers
</div></div></div><div><h5 class="jobSectionHeader">Other</h5>
<div><div><div>Languages
English: C2 Proficient
</div></div><div><div>Seniority
Lead</div></div></div></div></div>
 <div><div><div>Abu Dhabi, United Arab Emirates
</div>Req. VR-123799
</div><div></div><div><div>C#/VB.NET
</div><div>BCM Industry
</div><div>07/07/2026
</div><div>Req. VR-123799</div></div></div>

Principal Full-Stack Architect (.NET & Cloud)

Deeplight

<div>DeepLight AI is a specialist AI and data consultancy dedicated to transforming the regional corporate landscape through bespoke, high-impact intelligent systems. Based in the UAE, we partner with organizations across diverse sectors&mdash;with a deep-rooted expertise in Financial Services and Banking&mdash;to bridge the gap between complex data and actionable business strategy.
At DeepLight, we don't believe in &quot;off-the-shelf&quot; fixes. We deliver tailored AI solutions designed to integrate seamlessly into existing enterprise architectures, ensuring that innovation is both scalable and secure. From building robust data foundations to deploying sophisticated AI platforms, we empower our clients to lead in an increasingly automated world.
As a Senior AI Engineer, you will drive the design, development, and deployment of production-grade Artificial Intelligence and Generative AI solutions. This role sits at the intersection of cutting-edge research and enterprise-scale application engineering, specifically focused on delivering high-impact, secure, and performant intelligent systems for premier clients in regulated spaces like financial services and banking.
You will act as a technical pillar within the AI squad&mdash;collaborating with Data Architects, UI Engineers, and delivery leads to transform complex business requirements into robust, production-ready AI agents and pipelines. This role demands exceptional technical mastery, a deep commitment to architectural integrity, and a proactive approach to solving ambiguous data challenges.
Key ResponsibilitiesGenerative &amp; Agentic AI Engineering<ul><li>
Cognitive Systems Architecture: Design, build, and optimize enterprise-grade Generative AI applications and multi-agent frameworks capable of complex reasoning and autonomous task execution.</li><li>
Knowledge Retrieval Systems: Architect and maintain scalable Retrieval-Augmented Generation (RAG) pipelines utilizing advanced vector databases and semantic search strategies.</li><li>
Advanced Prompt Engineering: Develop and systematically evaluate advanced prompting techniques, guardrails, and context-window management strategies to ensure predictable, secure model behavior.</li></ul>
Deep Learning &amp; Model Optimization<ul><li>
Core Modeling &amp; Execution: Train, fine-tune, and deploy deep learning models across both Natural Language Processing (NLP) and Computer Vision (CV) domains.</li><li>
Open-Source &amp; Cloud Integration: Evaluate and deploy both proprietary cloud models (e.g., GPT, Claude) and open-source foundation models, balancing performance, latency, and cost.</li><li>
Edge &amp; Inference Optimization: Convert and optimize models for efficient production deployment and runtime inference using formats like ONNX.</li></ul>
Data &amp; MLOps Infrastructure<ul><li>
Data Processing Pipelines: Architect and refine complex, highly performant data preprocessing and feature engineering pipelines for unstructured and structured data.</li><li>
Database Governance: Design and optimize high-throughput queries across relational SQL databases and specialized NoSQL/Vector data stores.</li><li>
Rigorous Evaluation: Establish robust, data-driven model evaluation frameworks to continuously benchmark accuracy, drift, latency, and safety in production.</li></ul>
As an AI consultancy, our greatest asset is the expertise of our people.
 
While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deeplight.
 
We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills.
 
You will be the face of our firm, tasked with building trust, articulating the &quot;why&quot; behind your technical decisions, and effectively &quot;selling&quot; your vision to high-level stakeholders.
 
If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in. 
Requirements 
We need you to have:<ul><li>
A proven track record of designing, evaluating, and operating AI/ML models in high-availability enterprise or production environments.</li><li>
Demonstrated professional or research experience spanning both Natural Language Processing (NLP) and Computer Vision (CV).</li><li>
Hands-on experience leveraging enterprise cloud AI infrastructures (such as Azure AI Studio or AWS Bedrock) to deploy foundation models.</li></ul>
AI, Modeling &amp; Frameworks<ul><li>
Deep conceptual and practical understanding of Large Language Models (LLMs), agentic workflows, function calling, and embedding models.</li><li>
Expert proficiency in PyTorch and TensorFlow for building, training, and troubleshooting deep neural networks.</li><li>
A practical understanding of model compilation, quantization, and deployment optimization via ONNX runtime.</li><li>
High proficiency in configuring and querying Vector Databases (e.g., Azure DocumentDB, Elasticsearch, Faiss) alongside extensive knowledge of enterprise SQL and NoSQL architectures.</li></ul>
Software Engineering &amp; Core Tools<ul><li>
Perfect-tier coding skills in Python, with a command of asynchronous programming, design patterns, and clean, modular code architecture.</li><li>
Advanced capabilities in processing massive datasets utilizing standard data ecosystems (e.g., Pandas, NumPy, Polars, or PySpark)</li></ul>
It would also be great if you had: 
<ul><li>
An MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a highly related quantitative field.</li><li>
Prior experience engineering AI solutions within banking, fintech, or highly regulated corporate environments (e.g., familiarity with data privacy, compliance, and secure financial data models).</li><li>
Familiarity with framework libraries such as LangChain, LlamaIndex, or AutoGen for agentic workflow construction.</li></ul> 

Benefits 
The benefits you'll enjoy as part of this role include: 
<ul><li>
Competitive salary
</li><li>Comprehensive personal health insurance
</li><li>Visa Sponsorship for the successful individual</li><li>
Professional development and certification support</li><li>
Subscription reimbursement relating to your role</li><li>
Opportunity to work on cutting-edge AI projects</li><li>
Monthly Employee Incentive program</li><li>
Career advancement opportunities in a rapidly growing AI company</li></ul> 
This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients. 
 
At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.
Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.
If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.</div>

Senior AI Engineer

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