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ai engineer global markets

DICETEK LLC

<div>The AI Engineer will be responsible for the design, development, deployment, and support of AI-driven solutions within the Global Markets domain. The role requires strong technical expertise in machine learning, generative AI, and agentic AI frameworks, with a focus on delivering scalable, secure, and future-proof solutions aligned with enterprise architecture standards.
The candidate should possess a bachelor&rsquo;s degree in information systems
General expectation:<ul><li>Collaborate with business and technology stakeholders to understand analytical needs and translate them into AI solutions.</li><li>Design and implement AI/ML pipelines, including data ingestion, model training, evaluation, and deployment.</li><li>Develop and maintain GenAI and agentic AI applications using modern frameworks and cloud-native tools.</li><li>Ensure solutions are aligned with enterprise AI governance, security, and compliance standards.</li><li>Provide production support and continuous improvement for deployed models and applications.</li></ul>
- Contribute to knowledge sharing and capability building within the team.- Respect timelines<ul><li>Good communication skills</li></ul> 
Skillset and experience:<ul><li>8+ years of experience in AI/ML engineering, with recent focus on GenAI and agentic AI.</li><li>Hands-on experience on AWS and Azure.</li><li>Hands-on experience with CrewAI, LangChain, LangGraph, RAG pipelines, and LLM fine-tuning.</li><li>Strong programming skills in Python and experience with FastAPI, REST APIs, and microservices.</li><li>Proficiency in cloud platforms (AWS, Azure) and MLOps tools (Vertex AI, SageMaker, MLflow).</li><li>Experience with DevOps practices including CI/CD, containerization (Docker), and infrastructure-as-code (Terraform, CloudFormation).</li><li>Familiarity with vector databases (e.g., FAISS, ChromaDB) and graph-based reasoning (e.g., Neo4j).</li></ul>
Exposure to financial services or Global Markets, specifically Murex is a plus.</div>

AI Engineer – Global Markets

<div>Role Summary
The Senior Engineer &ndash; Data Governance &amp; Platform Lead (IB&amp;M) is a hands-on senior technical role responsible for defining, implementing, and governing the IB&amp;M Data Platform with a strong focus on data governance, quality, lineage, security, and platform standards.
The role will work closely with Global Markets, Investment Banking, Risk, Compliance, and Analytics teams to ensure data is trusted, compliant, and scalable across the enterprise. This is not a people‑management role but requires strong technical leadership and ownership across the data lifecycle.
Key Responsibilities<ul><li>
Define and govern the IB&amp;M Data Platform, ensuring strong data governance, quality, lineage, security, and compliance.
</li><li>Lead the design and implementation of scalable data platform standards across Azure Lakehouse (ADLS, Databricks, Delta Lake).
</li><li>Provide technical leadership on data architecture, platform engineering, and governance best practices.
</li><li>Collaborate with Global Markets, Risk, Compliance, Analytics, and engineering teams to deliver trusted and compliant data solutions.
</li><li>Review solution designs, establish platform standards, and ensure scalability, performance, security, and regulatory compliance.</li></ul> 
Experience<ul><li>10+ years of experience in Data Engineering, Data Platforms, or Data Architecture</li><li>Proven experience leading data governance initiatives in large, regulated environments (Banking / Financial Services preferred)</li><li>Strong background supporting Global Markets / Investment Banking data domains is highly desirable</li></ul>
Technical Skills<ul><li>Strong hands-on experience with:
</li></ul>o Azure Data Lake (ADLS)
o Databricks / Delta Lake / Lakehouse architectures
o Data quality, schema enforcement, and validation frameworks<ul><li>Experience with data cataloging and governance tools (e.g., Unity Catalog, Informatica Axon or similar)
</li><li>Solid understanding of:
</li></ul>o Data modeling (analytical and canonical models)
o Metadata management and lineage
o Secure data access and entitlements<ul><li>Good understanding of AI/ML and analytics enablement within governed data platforms</li></ul>
Soft Skills<ul><li>Strong ownership mindset with ability to work independently</li><li>Excellent stakeholder management and communication skills</li><li>Ability to translate regulatory and business requirements into technical solutions</li><li>Comfortable working in complex, multi‑vendor, enterprise environments</li></ul></div>

Data Governance & Platform Lead – IB&M

Lunate

<div>
 
 
 Firm Overview
 
 
 
 
 
 
 Lunate is a new Abu Dhabi-based, Partner-led, independent global alternative investment manager with more than 250 employees and $115 billion of assets under management. Lunate invests across the entire private markets spectrum including buyouts, growth equity, early and late-stage venture capital, private credit, real assets, and public equities and public credit. Lunate aims to be one of the world&rsquo;s leading private markets solutions providers through SMAs and multi-asset class funds, seeking to generate best-in-class risk-adjusted returns for its clients.
 
 
 
 
 
 
 Job Purpose
 
 
 
 
 
 
 The Senior Data Engineer will be the first dedicated internal data engineering hire in Lunate&rsquo;s Data &amp; AI function. This role is responsible for building dependable ingestion and transformation pipelines into Snowflake, shaping high-quality, well-modelled datasets that power reporting, operations, and AI-enabled products. You will work closely with the Head of Data &amp; AI and partner with Infrastructure (who own Snowflake account and platform setup) to deliver a modern, data-as-code engineering practice with strong controls, testing, and repeatability, supporting both BI and AI/Agentic workloads.
 
 
 
 
 
 
 Key Duties and Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Build and own ingestion pipelines into Snowflake using modern ELT patterns (Fivetran or equivalent, plus custom ingestion where needed), handling schema drift and source changes safely.
 </li>
 <li>
 Leverage AI Tools to design and automate our pipelines.
 </li>
 <li>
 Implement a layered data architecture (raw, standardised, business) that preserves immutability, auditability, and supports reprocessing and backfills.
 </li>
 <li>
 Develop transformations as version-controlled code (SQL and Python) using dbt or equivalent tooling.
 </li>
 <li>
 Apply pragmatic data modelling practices, using dimensional (Kimball) or relational approaches where appropriate.
 </li>
 <li>
 Build data quality and reconciliation into pipelines, with automated checks and visible quality signals.
 </li>
 <li>
 Operate pipelines like software: CI/CD, automated testing, peer review, and controlled promotion across environments.
 </li>
 <li>
 Optimise Snowflake usage for performance and cost, working with Infrastructure on governance controls.
 </li>
 <li>
 Partner with BI practitioners and AI engineers to deliver AI-ready datasets with consistent semantics and clear lineage.
 </li>
 <li>
 Collaborate with investment, operations, and finance teams to translate requirements into robust data products.
 </li>
 <li>
 Contribute to engineering standards, patterns, and documentation as the data function scales.
 </li>
 </ul>
 
 
 
 
 
 Qualifications and Experience
 
 
 
 
 
 <ul>
 <li>
 6+ years of professional data engineering experience delivering production pipelines.
 </li>
 <li>
 Strong experience with Snowflake&rsquo;s full suite of products &ndash; especially core functionality.
 </li>
 <li>
 Hands-on experience with dbt, including testing and environment management.
 </li>
 <li>
 Familiarity with modern ingestion tools such as Fivetran.
 </li>
 <li>
 Strong grounding in data modelling fundamentals (Kimball and relational).
 </li>
 <li>
 Python-native, comfortable writing production-quality pipeline and orchestration code.
 </li>
 <li>
 Strong software engineering discipline applied to data (Git, CI/CD, automated testing).
 </li>
 <li>
 Experience building replayable, idempotent pipelines with backfill support.
 </li>
 <li>
 Financial services experience preferred, with understanding of audit, restatement, and as-of data concepts.
 </li>
 </ul>
</div>

Senior Data Engineer

HTC Global Services

<div>
 
 Exciting Opportunity Alert! 🌟 HTC Global Services is hiring
 
 AI Engineer
 
 for an 1-year extendable contract in Abu Dhabi, UAE (Onsite).
 
 
 
 
 
 HTC Global Services - a leading CMM level 5 global provider of innovative IT and Business Process Services and Solutions since 1990 with headquarters in Troy, Michigan, USA.
 
 
 
 
 
 
 
 About the Role:
 
 
 
 
 We are seeking an AI Engineer (Innovation) with 6+ years of experience with dtrong programming experience in Python. Expertise in Machine Learning, Deep Learning, NLP, and Generative AI. Hands-on experience with OpenAI, Azure OpenAI, LangChain, Semantic Kernel, AutoGen, or similar Agentic AI frameworks.
 
 
 
 
 Requirements:
 
 
 
 <ul>
 <li>
 Design and develop AI/ML and Generative AI solutions.
 </li>
 <li>
 Build predictive models for demand forecasting, revenue optimization, dynamic pricing, ancillary revenue growth, and passenger behavior analysis.
 </li>
 <li>
 Develop and deploy LLM-based applications using RAG, Vector Databases, Prompt Engineering, and Agentic AI frameworks.
 </li>
 <li>
 Build intelligent recommendation and personalization engines.
 </li>
 <li>
 Develop scalable AI pipelines and integrate AI models with enterprise applications and operational systems.
 </li>
 <li>
 Deploy and manage AI solutions on Azure cloud platforms.
 </li>
 <li>
 Collaborate with Data Engineers, Data Scientists, Product Owners, and Business Stakeholders to translate business requirements into AI solutions.
 </li>
 <li>
 Ensure model performance, scalability, security, governance, and compliance standards.
 </li>
 </ul>
 
 
 
 Required Skills:
 
 
 
 <ul>
 <li>
 Experience building RAG architectures and Vector Databases.
 </li>
 <li>
 Strong knowledge of LLMs, Prompt Engineering, Fine-tuning, and AI Evaluation frameworks.
 </li>
 <li>
 Experience with Azure AI Services, Azure Databricks, Azure Machine Learning, Azure Data Factory, and Azure DevOps.
 </li>
 <li>
 Experience with MLOps, CI/CD, model deployment, monitoring, and governance.
 </li>
 <li>
 Knowledge of data engineering concepts, APIs, microservices, and event-driven architectures.
 </li>
 <li>
 Familiarity with SQL, Spark, and large-scale data processing.
 </li>
 </ul>
 
 
 
 
 Interested candidates please do share your updated CV to mubeenakamal.basha@htcinc.com mentioning your Current CTC, expected CTC and notice period details.
 
 
 
 
 
 #HTCGlobalServices #ITJobs #hiring #lookingforjob #careers #jobs #immediatejoiner #recruitment #technology #jobseekers #interview #lookingforjobchange #newjob #AIEngineer #LLM #RAG #MCP #fastMCP #Python #LangGraph #LangChain #AzureAI
 
</div>

AI Engineer

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

Acenet consulting

<div><div>Experience: 5 to 8 years
 
Location: Abu Dhabi, Bengaluru, Gurgaon, Pune
 
Job code: 101532
 
Posted on: Jun 24, 2026 
</div> 
About Us: 
AceNet Consulting is a fast-growing global business and technology consulting firm leveraging a consultative approach, deep domain expertise and strong technology capabilities across business transformation, IT strategy &amp; architecture, digital transformation, data engineering &amp; analytics, AI/ML, cloud &amp; infrastructure, enterprise applications and emerging technologies to deliver value to our global clients. AceNet&rsquo;s marquee clients include Tier-1 and Tier-2 banking &amp; financial services, asset &amp; wealth management, healthcare, consumer retail, eCommerce &amp; logistics, engineering, government &amp; public sectors, consulting and technology firms. With presence across Abu Dhabi UAE, Texas USA and India (Bangalore, Gurgaon &amp; Pune), AceNet brings strong consulting and delivery capabilities across project staffing, managed services, outsourcing and offshoring.
About the Role 
We are looking for a highly motivated AI/ML Engineer with hands-on experience in designing and developing intelligent AI-driven solutions. The ideal candidate should have strong expertise in Conversational AI, Prompt Engineering, Retrieval-Augmented Generation (RAG), and Python-based application development. The role requires a curious mindset, strong analytical skills, and the ability to quickly learn and adapt to emerging AI technologies.
<div>Key Responsibilities: 
<ul><li>Design, develop, and deploy AI/ML solutions for enterprise applications.</li><li>Build and optimize Conversational AI solutions using Large Language Models (LLMs).</li><li>Create, test, and refine prompts to improve AI model performance and response quality.</li><li>Design and implement Retrieval-Augmented Generation (RAG) pipelines leveraging both structured and unstructured data sources.</li><li>Develop and maintain RESTful APIs to integrate AI services with business applications.</li><li>Perform web content extraction and data collection using screen-scraping/web-scraping techniques.</li><li>Collaborate with cross-functional teams to understand business requirements and translate them into scalable AI solutions.</li><li>Troubleshoot, optimize, and improve existing AI models and workflows.</li><li>Stay updated with the latest advancements in AI/ML, Generative AI, and emerging technologies.</li></ul></div>
<div>Required Skills &amp; Qualifications: 
<ul><li>5&ndash;8 years of overall IT experience with at least 3&ndash;4 years of relevant experience in AI/ML development.</li><li>Strong proficiency in Python programming.</li></ul></div>
<div>Hands-on experience with: 
<ul><li>Conversational AI platforms and frameworks</li><li>Prompt Engineering / Prompt Creation</li><li>Retrieval-Augmented Generation (RAG)</li><li>Working with both structured and unstructured data sources</li><li>Experience in building and consuming REST APIs.</li><li>Experience with web page content extraction, web scraping, and screen-scraping techniques.</li><li>Strong problem-solving, debugging, and analytical skills.</li><li>Excellent communication and collaboration abilities.</li><li>Self-driven individual with strong curiosity, eagerness to learn, and a focus on delivering high-quality outcomes.</li></ul></div>
<div>Preferred Skills: 
<ul><li>Understanding of Agentic AI concepts and AI orchestration frameworks.</li><li>Exposure to multi-agent systems and workflow automation.</li><li>Experience with vector databases, embeddings, and knowledge retrieval systems.</li><li>with cloud platforms such as AWS, Azure, or Google Cloud.</li></ul></div>
<div>Why Join Us: 
<ul><li>Opportunities to work on transformative projects, cutting-edge technology and innovative solutions with leading global firms across industry sectors.</li><li>Continuous investment in employee growth and professional development with a strong focus on up &amp; re-skilling.</li><li>Competitive compensation &amp; benefits, ESOPs and international assignments.</li><li>Supportive environment with healthy work-life balance and a focus on employee well-being.</li><li>Open culture that values diverse perspectives, encourages transparent communication and rewards contributions.</li></ul></div>
How to Apply: 
If you are interested in joining our team and meet the qualifications listed above, please apply and submit your resume highlighting why you are the ideal candidate for this position.</div>

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384 ai engineer global markets jobs In Abu Dhabi

AI Engineer – Global Markets

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