mechanical engineer

devops engineer

data scientist

estimation engineer

project engineer

deep 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)

Saal.ai

<div>
 
 
 Job Purpose
 
 
 
 As a Data Scientist at SAAL.ai, you will apply machine learning and deep learning techniques to solve real-world business problems across numeric and text-based analytics. You will work across the full data science lifecycle&mdash;from data acquisition and feature engineering to model development and deployment&mdash;collaborating closely with engineering, product, and DevOps teams to deliver customer-centric AI solutions.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Develop and deliver high-quality machine learning and deep learning models across a broad range of analytics use cases.
 </li>
 <li>
 Understand the practical scope and constraints of AI models within products and apply appropriate modeling techniques to ensure business relevance and technical robustness.
 </li>
 <li>
 Acquire data from diverse sources, performing data exploration and preprocessing on structured and unstructured datasets, conducting feature engineering, evaluating algorithms and architectures, and iteratively refining models to improve performance.
 </li>
 <li>
 Identify valuable data sources and automate data collection and preparation processes where possible.
 </li>
 <li>
 Build, fine-tune, and maintain machine learning pipelines, integrate algorithms and packages into the platform, and contribute new models to the platform marketplace.
 </li>
 <li>
 Collaborate closely with engineering and DevOps teams to support model deployment and operationalization.
 </li>
 <li>
 Contribute to applied research activities, propose data-driven solutions to business challenges, and work with product, support, and client-facing teams to ensure successful rollout of AI solutions into trials and general availability.
 </li>
 </ul>
 
 
 
 
 
 Key Skills
 
 
 <ul>
 <li>
 Strong foundation in the theory and applied practice of machine learning and deep learning. Experience developing pipelines for structured and unstructured data.
 </li>
 <li>
 Hands-on experience with deep learning frameworks such as TensorFlow and PyTorch, and machine learning libraries such as scikit-learn.
 </li>
 <li>
 Proficiency in Python, with working knowledge of Java or R.
 </li>
 <li>
 Experience developing and exposing models through RESTful APIs and containerized deployments using Docker.
 </li>
 <li>
 Strong coding practices, including appropriate use of data structures and clean, maintainable code.
 </li>
 <li>
 Applied experience in NLP, including the use of transformer-based models and libraries such as Hugging Face, spaCy, or Gensim. Familiarity with SQL, Pandas, Apache Spark, and data processing at scale.
 </li>
 <li>
 Experience using ML lifecycle tools such as MLflow.
 </li>
 <li>
 Strong analytical thinking, communication skills, and the ability to present technical concepts clearly to internal and external stakeholders.
 </li>
 <li>
 Ability to work collaboratively across multidisciplinary teams.
 </li>
 </ul>
 
 
 
 
 
 Desirable Skills
 
 
 
 Experience working with large language models (LLMs), including offline deployment scenarios. Exposure to cloud-based environments (AWS, GCP, Azure). Experience with data visualization tools and collaborative environments such as Jupyter Notebooks and Git-based workflows. Domain experience with education or finance datasets is an advantage.
 
</div>

Data Scientist

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

Avrioc Technologies

<div>
 
 
 Introduction
 
 
 
 As part of a cross-functional team of engineers, data scientists, and product owners you will be responsible for designing, implementing, optimizing, and evaluating our product (specific product language here) algorithms. If you love seeing your ideas blossom through their whole life cycle from concept to governing the interaction with millions of users - then Avrioc is the place to be for you!
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 MS degree in Statistics, Math, Data Analytics, or a related quantitative field
 </li>
 <li>
 4+ years Professional experience in Advanced Data Science, such as predictive modeling, statistical analysis, machine learning, text mining, geospatial analytics, time series forecasting, optimization
 </li>
 <li>
 Experience with one or more Advanced Data Science software languages (R, Python, Scala, SAS)
 </li>
 <li>
 Hand on experience with Deep Learning models such as Image classification, Object Detection, Style transfer and similar
 </li>
 <li>
 Hands-on experience with any of Python DL libraries such as PyTorch, TensorFlow on keras
 </li>
 <li>
 Hands-on experience with working on CUDA backend
 </li>
 <li>
 Hands-on experience with Linux system terminal, shell scripting
 </li>
 <li>
 Working knowledge of ELK stack and Message Broker queues
 </li>
 <li>
 Proven ability to deploy machine learning models from the research environment (Jupyter Notebooks) to production via procedural or pipeline approaches
 </li>
 <li>
 Comfortable with cloud-based platforms (AWS, Azure, Google)
 </li>
 <li>
 Good planning abilities in order to accurately make project timeline estimates.
 </li>
 <li>
 Ability to show initiative and work independently with minimal direction.
 </li>
 <li>
 Demonstrate a desire to remain current with industry technologies and standards.
 </li>
 <li>
 Self-starter and strong interpersonal skills.
 </li>
 </ul>
 
 
 
 
 
 Nice to have
 
 
 <ul>
 <li>
 Comfortable with cloud-based platforms (AWS, Azure).
 </li>
 <li>
 Good communication and presentation skills.
 </li>
 <li>
 Experience with media data (platforms and customer data from either the media agency, technology, or brand side).
 </li>
 <li>
 Good appreciation for the Agile/Scrum methodology
 </li>
 </ul>
 
 
</div>

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

NodeShift

<div>
 
 
 About NodeShift
 
 
 
 
 
 
 NodeShift is a fast-growing AI infrastructure startup headquartered in Al Maryah Island, Abu Dhabi, the UAE&rsquo;s most prestigious innovation and financial district with a second office in Qatar Financial Centre (QFC), Doha.
 
 
 
 
 
 We design and operate sovereign cloud and generative AI platforms for governments, banks, and national enterprises that require full data control and compliance. Our customers include the Ministry of Economy of the UAE, the Qatar Development Bank, and the Central Bank of the UAE, among others.
 
 
 
 
 
 NodeShift AI &ndash; an enterprise-grade, on-premise generative AI platform featuring 140+ Arabic and English models, built-in governance, and over 80 enterprise integrations, enabling organizations to create secure, private ChatGPT-like environments within their own infrastructure.
 
 
 
 
 
 Founded by a leadership team from Microsoft, X (formerly Twitter), Tesla, and Cisco, and built by a world-class engineering team including Oxford graduates, NodeShift combines global expertise with regional purpose.
 
 
 
 
 
 We&rsquo;re expanding rapidly across the GCC, supporting central banks, ministries, telecoms, and data center operators and shaping the next era of sovereign AI and cloud computing in the region.
 
 
 
 
 
 Joining NodeShift means joining a team that&rsquo;s building the infrastructure of national AI sovereignty - innovative, impactful, and proudly homegrown in the Gulf.
 
 
 
 
 
 Read more about us on TechCrunch.
 
 
 
 
 
 
 Role Description
 
 
 
 
 
 
 We&rsquo;re looking for a highly skilled
 
 DevOps Engineer
 
 to join our growing team. You&rsquo;ll act as the bridge between our product, engineering, and customers - helping organizations design, deploy, and optimize technical solutions that leverage our platform. This is a hands-on, cross-functional role that requires a deep understanding of modern cloud architectures, APIs, and integration patterns.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Collaborate with clients and internal teams to design scalable, secure, and high-performance solutions.
 </li>
 <li>
 Lead technical discovery sessions and translate business needs into actionable architecture.
 </li>
 <li>
 Build proofs-of-concept (POCs), demos, and technical documentation for customers and partners.
 </li>
 <li>
 Work closely with engineering to ensure successful implementations and product fit.
 </li>
 <li>
 Support pre-sales engagements by presenting technical capabilities and addressing customer requirements.
 </li>
 <li>
 Troubleshoot integration issues and provide guidance on best practices.
 </li>
 <li>
 Gather customer feedback and contribute to product roadmap discussions.
 </li>
 <li>
 Deliver enablement sessions, workshops, and onboarding for partners or enterprise clients.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 3+ years of experience in a DevOps, SRE, Solutions Engineer or Sales Engineer / Cloud Engineer role.
 </li>
 <li>
 Strong technical understanding of modern infrastructure: Kubernetes, Docker, REST / GraphQL APIs, and CI/CD workflows.
 </li>
 <li>
 Solid scripting or programming skills (Python, Go, JavaScript, or similar).
 </li>
 <li>
 Excellent communication and presentation skills, with the ability to explain complex ideas clearly.
 </li>
 <li>
 Ability to work autonomously in fast-moving startup or enterprise environments.
 </li>
 </ul>
 
 
 
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Experience with identity and access management (OIDC, SAML, OAuth2).
 </li>
 <li>
 Understanding of networking, VPN (WireGuard, IPSec), or distributed systems.
 </li>
 <li>
 Knowledge of observability tools (Grafana, Prometheus, ELK, etc.).
 </li>
 <li>
 Prior work in AI infrastructure, data platforms, or enterprise SaaS solutions.
 </li>
 <li>
 Contributions to open-source projects or technical writing (blogs, docs, etc.).
 </li>
 </ul>
 
 
 
 
 
 What do we have to offer you?
 
 
 <ul>
 <li>
 Hybrid office / remote-working practices
 </li>
 <li>
 Competitive salary
 </li>
 <li>
 Learning and Development budget
 </li>
 <li>
 24 days PTO
 </li>
 <li>
 Become part of the founding team
 </li>
 <li>
 Real career opportunities with the opportunity to grow quickly in seniority as the team scales&nbsp;
 </li>
 <li>
 Work colleagues that are as smart, hardworking and driven with backgrounds from FAANG companies and leading universities
 </li>
 <li>
 Transparent company culture, open to feedback where you can wear multiple hats at once
 </li>
 </ul>
 
 
 
</div>

DevOps Engineer

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

Explore 296+ Deep learning engineer in Abu Dhabi this July. Find roles across top companies and apply now to boost your career.

296 deep learning engineer jobs In Abu Dhabi

AI Engineer (Innovation)

Data Scientist

Senior AI Engineer

Data Scientist

Data and AI Engineering Expert

DevOps Engineer

Solution Architect- Wealth Management