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Jaheziya

<div>
 
 About The Role
 
 
 
 Design, deploy, and manage scalable AI platforms and MLOps pipelines, ensuring the performance, reliability, scalability, and security of AI systems throughout their lifecycle.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, deploy, and maintain scalable AI platforms and MLOps pipelines.
 </li>
 <li>
 Manage AI infrastructure, deployment, and CI/CD pipelines.
 </li>
 <li>
 Monitor AI systems and machine learning models to ensure performance, reliability, and availability.
 </li>
 <li>
 Ensure the scalability, security, and operational stability of AI platforms.
 </li>
 <li>
 Automate model deployment, monitoring, and lifecycle management.
 </li>
 <li>
 Collaborate with data scientists and software engineers to operate AI solutions.
 </li>
 <li>
 Troubleshoot and optimize AI infrastructure and production environments.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
 </li>
 <li>
 3&ndash;8 years of relevant experience in AI systems engineering, MLOps, or machine learning platform engineering.
 </li>
 <li>
 Strong experience with Python, Docker, Kubernetes, and cloud platforms.
 </li>
 <li>
 Experience with CI/CD pipelines and machine learning frameworks.
 </li>
 <li>
 Experience managing AI infrastructure and deploying machine learning solutions.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with Azure ML, AWS SageMaker, or Vertex AI.
 </li>
 <li>
 Experience with Terraform or other Infrastructure as Code (IaC) tools.
 </li>
 </ul>
</div>

AI Systems & Machine Learning Operations (MLOps) Engineer

TALENTMATE

<div>
 
 Job Description
 
 
 
 
 About The Role
 
 
 
 Design, deploy and support scalable AI platforms and MLOps pipelines that enable reliable machine learning solutions.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and maintain MLOps pipelines.
 </li>
 <li>
 Automate model deployment and monitoring.
 </li>
 <li>
 Manage AI infrastructure and CI/CD pipelines.
 </li>
 <li>
 Collaborate with data scientists and software engineers.
 </li>
 <li>
 Monitor model performance and optimise reliability.
 </li>
 <li>
 Ensure security and scalability of AI platforms.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, AI, Data Science or related field.
 </li>
 <li>
 3&ndash;8 years' relevant experience.
 </li>
 <li>
 Experience with Python, Docker, Kubernetes and cloud platforms.
 </li>
 <li>
 Knowledge of CI/CD and machine learning frameworks.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with Azure ML, AWS SageMaker or Vertex AI.
 </li>
 <li>
 Terraform or Infrastructure as Code experience.
 
 
 </li>
 </ul>
 Job Details
 
 
 Role Level: Not Applicable Work Type: Full-Time Country: United Arab Emirates City: Abu Dhabi Company Website: https://jaheziya.ae/ Job Function: DevOps &amp; QA Company Industry/
 
 
 Sector: Emergency and Relief Services
 
 
 What We Offer
 
 
 
 About The Company
 
 
 
 Searching, interviewing and hiring are all part of the professional life. The TALENTMATE Portal idea is to fill and help professionals doing one of them by bringing together the requisites under One Roof. Whether you're hunting for your Next Job Opportunity or Looking for Potential Employers, we're here to lend you a Helping Hand.
 
 
 Report
 
 
 Disclaimer: talentmate.com is only a platform to bring jobseekers &amp; employers together. Applicants are advised to research the bonafides of the prospective employer independently. We do NOT endorse any requests for money payments and strictly advice against sharing personal or bank related information. We also recommend you visit Security Advice for more information. If you suspect any fraud or malpractice, email us at abuse@talentmate.com.
</div>

AI Systems And Machine Learning Operations MLOps Engineer

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 Full Stack AI Engineer, you will be the ultimate bridge between advanced data science and enterprise-scale software architecture. This role is designed for a rare breed of engineer: someone who possesses the deep mathematical and modeling background required to design advanced AI and Generative AI systems, paired with the full-stack infrastructure capabilities needed to deploy, containerize, scale, and monitor them across hybrid, cloud, and on-premise environments.
Operating within complex client landscapes&mdash;such as premier banking and financial institutions (e.g., ADCB)&mdash;you will own the full engineering lifecycle of AI applications. You will design secure, highly performant systems, orchestrate massive data pipelines, optimize cloud spend, and establish robust MLOps practices that guarantee production stability.
Key ResponsibilitiesEnd-to-End AI Architecture &amp; Full-Stack Design<ul><li>
Architect end-to-end, highly secure AI and Generative AI systems capable of running seamlessly across both secure on-premise data centers and public cloud infrastructures (Azure/AWS).</li><li>
Design, build, and optimize high-throughput, secure APIs to serve complex AI models and agentic workflows to consuming client applications.</li><li>
Seamlessly integrate proprietary cloud foundation models (GPT, Claude, Gemini) and fine-tuned open-source models into unified software ecosystems.</li></ul>
Deep Learning &amp; Advanced AI Engineering<ul><li>
Leverage a deep theoretical understanding of Transformers, PyTorch, and TensorFlow to implement, evaluate, and optimize deep learning models across NLP and Computer Vision domains.</li><li>
Design scalable knowledge retrieval frameworks using embedding models and enterprise-grade Vector Databases (e.g., Azure DocumentDB, Elasticsearch, Faiss).</li><li>
Build and evaluate robust systematic prompting frameworks and compile complex models using ONNX for optimized, low-latency production inference.</li></ul>
Infrastructure, MLOps &amp; FinOps<ul><li>
Own the containerization and scaling of AI services utilizing Docker and Kubernetes clusters across development and production environments.</li><li>
Build and automate robust MLOps continuous integration and deployment pipelines to track model lineage, versions, evaluations, and production drift.</li><li>
Implement strict FinOps practices to track, monitor, and radically optimize token usage, cloud compute consumption, and inferencing costs.</li><li>
Architect and optimize large-scale data processing systems using modern Big Data tools to feed raw information into AI training and embedding workflows.</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>
Extensive experience designing, launching, and managing containerized AI/ML or data-intensive applications in highly regulated enterprise environments.</li><li>
A proven track record applying deep learning models across both Natural Language Processing (NLP) and Computer Vision (CV) fields.</li><li>
Practical experience implementing production-grade model monitoring frameworks and optimizing complex cloud/token expenditure.</li><li>
Deep operational command of Docker and enterprise Kubernetes infrastructure for running distributed AI applications.</li><li>
Expert-level knowledge of Azure (or alternative major clouds) alongside a strong architectural grasp of on-premise deployment constraints, data security, and network topologies.</li><li>
Strong proficiency in Big Data toolsets and modern API gateway designs.</li><li>
A rigorous, foundational grasp of transformer architectures, embedding mechanics, and deep learning implementations via PyTorch/TensorFlow.</li><li>
High proficiency across SQL, NoSQL, and Vector Database engines.</li><li>
&quot;Perfect-tier&quot; software engineering skills in Python and advanced data processing techniques.</li></ul>
It would also be great if you have:<ul><li>
An MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a highly relevant quantitative discipline.</li><li>
Deep domain experience within banking, understanding strict data residency laws, financial compliance protocols, and legacy core banking interactions.</li><li>
Practical experience with agentic frameworks (e.g., LangChain, LlamaIndex, AutoGen) and modern cloud MLOps suites (e.g., Azure AI Studio, Kubeflow).</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 Full Stack 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

<div>
 
 About The Role
 
 
 
 Design, deploy, and maintain scalable AI and machine learning systems that deliver secure, reliable, and high-performing AI solutions. Ensure efficient model serving, deployment, monitoring, and operational excellence across AI environments.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, deploy, and maintain scalable AI/ML systems and infrastructure.
 </li>
 <li>
 Develop and manage MLOps pipelines for automated model deployment and monitoring.
 </li>
 <li>
 Ensure the performance, reliability, security, and scalability of AI platforms.
 </li>
 <li>
 Deploy, serve, and optimize machine learning and generative AI models for production environments.
 </li>
 <li>
 Build and maintain CI/CD pipelines for AI applications.
 </li>
 <li>
 Manage containerized AI applications using Docker and Kubernetes.
 </li>
 <li>
 Collaborate with data scientists, software engineers, and business stakeholders to operationalize AI solutions.
 </li>
 <li>
 Monitor AI system performance, reliability, and availability, implementing continuous improvements.
 </li>
 <li>
 Troubleshoot production issues and optimize AI infrastructure.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
 </li>
 <li>
 3&ndash;8 years of experience in AI systems engineering, MLOps, or machine learning platform engineering.
 </li>
 <li>
 Strong programming skills in Python.
 </li>
 <li>
 Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
 </li>
 <li>
 Hands-on experience with Docker, Kubernetes, and containerized deployments.
 </li>
 <li>
 Experience designing and maintaining CI/CD pipelines.
 </li>
 <li>
 Knowledge of distributed systems and scalable AI infrastructure.
 </li>
 <li>
 Experience deploying and operationalizing machine learning and generative AI solutions.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with Azure Machine Learning, AWS SageMaker, or Google Vertex AI.
 </li>
 <li>
 Experience with Infrastructure as Code (Terraform or similar).
 </li>
 <li>
 Familiarity with AI monitoring, observability, and model lifecycle management.
 </li>
 <li>
 Relevant cloud or AI certifications.
 </li>
 </ul>
</div>

Artificial Intelligence (AI) & Machine Learning Engineer

HTC Global Services

<div>
 
 Job Description
 
 
 
 
 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>
</div>

AI Engineer (Innovation)

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 Engineer to design, build, and deploy production-grade AI systems &mdash; primarily LLM-powered applications, RAG pipelines, and agentic workflows &mdash; that solve real client business problems in the UAE. The role combines applied AI expertise with solid software and data engineering foundations, with hands-on ownership from prototype to production and hypercare.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and deliver end-to-end LLM applications: scope the use case, build, evaluate, deploy, and hand over reliable, observable services.
 </li>
 <li>
 Build and optimize RAG pipelines: data parsing, ingestion, chunking, embeddings, vector search, re-ranking, and context-window optimization.
 </li>
 <li>
 Design and orchestrate agentic workflows for reasoning, planning, and task execution.
 </li>
 <li>
 Build evaluation and observability: define metrics (accuracy, latency, cost-per-task), run eval pipelines, and monitor systems in production.
 </li>
 <li>
 Integrate AI components into client applications via secure backend APIs; collaborate with data, software, and DevSecOps teams.
 </li>
 <li>
 Engineer the supporting data layer: pipelines, feature/embedding stores, and data quality for AI workloads on cloud platforms.
 </li>
 <li>
 Manage the full lifecycle: deployment, monitoring, versioning, rollback readiness, and cost/performance optimization.
 </li>
 <li>
 Translate business problems into AI solutions and communicate model capabilities, limitations, and trade-offs clearly to clients and stakeholders.
 </li>
 <li>
 Maintain technical documentation, runbooks, and delivery artifacts across Design &amp; Align &rarr; Build &rarr; UAT &rarr; Production &amp; Hypercare.
 
 
 </li>
 </ul>
 
 Candidate Requirements
 
 
 
 <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>
 Strong Python and solid software engineering fundamentals.
 </li>
 <li>
 Hands-on LLM APIs (Anthropic, OpenAI, Azure OpenAI), including tokenization, latency, and cost control.
 </li>
 <li>
 Proven RAG architecture experience with vector databases (e.g., Azure AI Search, Qdrant, Chroma, Pinecone, FAISS).
 </li>
 <li>
 Experience with agent/orchestration frameworks (e.g., LangChain, LangGraph, CrewAI).
 </li>
 <li>
 Evaluation and observability skills for production AI (eval pipelines, LLM-as-judge, monitoring).
 </li>
 <li>
 Working knowledge of a major cloud AI/data stack (Azure, AWS, or GCP) and MLOps tooling (e.g., MLflow, Docker).
 </li>
 <li>
 Solid data engineering skills: SQL, distributed processing (e.g., Spark/Databricks).
 </li>
 <li>
 Strong collaboration and communication skills &mdash; able to work with both technical teams and senior client stakeholders.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
 </li>
 <li>
 3&ndash;6 years of experience building and shipping AI/ML solutions into production.
 </li>
 <li>
 Preferred certifications (nice to have): cloud AI certifications (Azure AI Engineer, AWS ML, Databricks GenAI Engineer).
 </li>
 </ul>
</div>

AI Engineer (6 months contract)

Explore 276+ Mlops engineer in Abu Dhabi this July. Find roles across top companies and apply now to boost your career.