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Presight

<div>
 
 
 The Opportunity:
 
 
 
 Presight AI is seeking a motivated and skilled Senior Fullstack Engineer to join our dynamic team building end-to-end AI-powered data processing and analytics platform for the enterprise.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 In this role, you will help build the distributed backend services and rich UI components that turn raw enterprise data into clean, normalized, governed, and ML/AI-enriched data products. These data products will serve as the foundation for high-performance classical BI analytics as well as modern agentic data engineering and analytics workflows. You may work across functional areas such as data profiling and quality, data governance, ETL pipelines, data warehouse capabilities, agentic data engineering, dashboards, spatial and geospatial analysis, and entity-centric analytics based on ontologies that model real-world objects, events, and relationships.
 
 
 
 
 
 
 Requirements:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in information technology, Computer Science, Engineering or related field
 </li>
 <li>
 Strong computer science and basic algorithms knowledge.
 </li>
 <li>
 5+ years of experience in Java, Python building backend services &amp; distributed systems.
 </li>
 <li>
 5+ years of experience building modern frontends with React and TypeScript.
 </li>
 <li>
 Experience designing and building large scale distributed fault tolerant services.
 </li>
 <li>
 Experience building: search, recommendations, or other advanced analytics systems.
 </li>
 <li>
 Strong knowledge about programming principles (SOLID).
 </li>
 <li>
 Strong understanding of data analytics fundamentals and knowledge of basic SQL.
 </li>
 <li>
 Proficient with agentic development tools.
 </li>
 </ul>
 
 
 
 
 
 Good to have:
 
 
 <ul>
 <li>
 data engineer experience with Databricks, Snowflake or MS Fabric.
 </li>
 <li>
 Worked with Clickhouse on OLAP/DWH workloads.
 </li>
 <li>
 Experience with batch and stream processing big data using Spark, Trino, Flink, Kafka, etc&hellip;
 </li>
 <li>
 Practical experience processing unstructured data with modern models &ndash; OCR, STT, NER, etc...
 </li>
 <li>
 Implemented complex analytics with BI tools such as Tableau, PowerBI or built your own.
 </li>
 <li>
 AI models, python notebook is something you like to play with as well.
 </li>
 <li>
 Have great communication skills and passion in technology and driving thing forward!
 </li>
 </ul>
</div>

Senior Full Stack Engineer

Fecundity Technologies

Role Overview: The Senior AI Engineer leads the technical delivery of one or more AWA use cases end-to-end, from Agent Profile definition through to production UAT sign-off. You own the architectural decisions within your use case domain: agent graph topology, confidence calibration, HITL threshold negotiation with the business, and the regression testing regime. You mentor AI Engineers and are the primary escalation point for complex LangGraph, LLM, and evaluation challenges. You are expected to identify failure modes before they reach production and to drive the adoption of new AWA capabilities across the use case portfolio.Key Responsibilities<ul><li>Use case technical ownership: Own the technical delivery of one or more AWA use cases from discovery through production; define the Agent Profile, Use Case Manifest, Data Manifest, and Tool Authorisation Matrix for each use case.</li><li>Architecture and design: Design LangGraph agent graph topologies for complex multi-agent pipelines including Supervisor-Worker fan-out, parallel execution, state compression, and cross-document reconciliation (3-way match).</li><li>Confidence calibration and HITL thresholds: Lead the AI Metric Baselines calibration process: measure ECE, derive HITL routing thresholds empirically, present threshold recommendations to business and risk teams, and own the signed AI Metric Baselines table.</li><li>Test strategy ownership: Own and execute the full AWA IDP Test Strategy for your use cases: all four testing bands (Model/Prompt/Agent/Security, Adversarial, Integration, UAT) through to sign-off.</li><li>Agent Regression Testing: Maintain the Golden Dataset and Regression Dataset for your use cases; configure CI/CD regression pipeline gates; review regression results after every model or prompt change.</li><li>Mentoring and code review: Mentor AI Engineers; conduct substantive technical code reviews of agent graphs, prompts, and MCP tool implementations; maintain AWA coding standards.</li><li>Stakeholder engagement: Present model quality metrics, STP rates, and HITL rates to Ops leads and business owners; recommend threshold adjustments with data-backed rationale.</li><li>New capability adoption: Evaluate and prototype new AI capabilities (new Azure AI Foundry models, new LangGraph features, new RAG patterns) for incorporation into the AWA accelerator catalogue.</li></ul>Required Skills and ExperienceTechnical &mdash; Essential<ul><li>5+ years Python development; 2+ years in production AI/ML engineering</li><li>Deep LangGraph or equivalent agentic framework experience: graph topology, state management, conditional edges, checkpoint-based recovery</li><li>LLM evaluation expertise: F1 measurement against ground truth, Expected Calibration Error (ECE), hallucination detection, confidence calibration</li><li>Prompt engineering at scale: versioned prompts, sensitivity analysis, few-shot dataset curation, PMS governance</li><li>RAG architecture: hybrid retrieval (BM25 + vector), re-ranking, chunk citation, grounding verification</li><li>Azure AI Foundry or equivalent LLM inference platform: PTU, PAYG, token budget management, APIM integration</li><li>Workflow orchestration: Orkes Conductor or Temporal &mdash; HITL wait tasks, retry policies, compensating transactions</li><li>CI/CD pipeline integration for ML: Azure DevOps, MLflow experiment tracking, model registry promotion</li></ul>Technical &mdash; Advantageous<ul><li>Computer vision model deployment and evaluation (object detection &mdash; TPR/TNR/IoU)</li><li>Azure AI Document Intelligence: form recogniser, custom models, layout analysis</li><li>Kubernetes / AKS: workload identity, namespace isolation, KEDA autoscaling</li><li>Apache Iceberg, DuckDB, and data contract patterns</li><li>Banking domain knowledge: cheque clearing, trade finance, KYC, AML</li></ul>Qualifications<ul><li>Bachelor's degree in Computer Science, AI/ML, or equivalent; Master's preferred</li><li>Azure AI Engineer Associate or equivalent certification</li><li>Demonstrable production AI deployments &mdash; case studies or public work highly valued</li></ul>Pay: AED21,000.00 - AED30,000.00 per monthWork Location: In person

Senior AI Engineer

Dizzaract FZ LLC

01. ABOUT THE COMPANYDizzaract is a product-driven company operating at the intersection of gaming, digital platforms, and AI. We build and scale multiple products &mdash; including Farcana, Gamed, and FAR Labs &mdash; each exploring a different space, but united by a shared approach: moving fast, staying curious, and focusing on things that people actually use. We operate as a collaborative, non-hierarchical team where ideas are valued based on their impact, not theirorigin, and where AI is embedded across everything we build &mdash; from infrastructure to product decisions.02. ABOUT THE ROLEWe&rsquo;re looking for a Senior AI Engineer to design and ship production AI systems powering GAMED.This role focuses on applied AI &mdash; not research for the sake of research. You&rsquo;ll work on recommendation systems, AI-driven moderation, retrieval systems, agentic workflows, ranking systems, and player-facing AI features integrated directly into the product ecosystem. You&rsquo;ll collaborate closely with Backend, Product, and Infrastructure teams to build scalable AI systems used by real users.03. WHO YOU ARE<ul><li>You think pragmatically about AI products and infrastructure.</li><li>You care about reliability, evaluation, and production quality.</li><li>You&rsquo;re comfortable building systems from experimentation to deployment.</li><li>You understand both model quality and infrastructure cost.</li><li>You enjoy solving applied ML problems in live environments.</li></ul>04. RESPONSIBILITIES<ul><li>Design and deploy AI-powered product features.</li><li>Build recommendation, ranking, moderation, and agent systems.</li><li>Develop and optimize RAG pipelines.</li><li>Work with modern LLM ecosystems and open-weight models.</li><li>Design evaluation frameworks and testing pipelines.</li><li>Optimize inference, retrieval, and deployment performance.</li><li>Collaborate closely with backend and infrastructure teams.</li></ul>05. REQUIREMENTS<ul><li>5+ years in engineering.</li><li>3+ years building applied ML/AI systems in production.</li><li>Strong Python expertise.</li><li>Experience with PyTorch or JAX.</li><li>Experience with LLMs, RAG, and agent systems.</li><li>Experience with vector databases and retrieval systems.</li><li>Understanding of model evaluation and deployment strategies.</li><li>Experience balancing quality, latency, and infrastructure cost.</li></ul>06. NICE TO HAVE<ul><li>RLHF / DPO / PPO experience.</li><li>Multi-agent systems.</li><li>Recommender systems at scale.</li><li>MLOps tooling.</li><li>AI safety / red-teaming experience.</li></ul>07. WHAT WE OFFER<ul><li>Real ownership and direct impact on a global AI infrastructure product.</li><li>Fast execution, low bureaucracy, and a highly collaborative, idea-driven team.</li><li>Exposure to cutting-edge AI, gaming platforms, and digital asset economies.</li><li>Competitive salary with performance-based incentives.</li><li>24 days annual leave, plus public holidays.</li><li>Health insurance.</li><li>Modern office in Yas Creative Hub.</li><li>Continuous learning through real-world problem solving &mdash; not just theory.</li><li>The opportunity to shape what you're working on and influence product direction.</li><li>A diverse, open-minded team where ideas are genuinely heard.</li></ul>Work Location: In person

DICETEK LLC

<div>Experience
10 -15 years
Skills -
Experience in working Full stack architecture
React JS, Python, Fast API as backend, Postgres SQL
Azure data factory - Backend data pipelines
TLS 1.2 or 1.3 implementation
SSO implementation
Lead the senior full stack developers
Design the Modules/ project and implement
Finops experience is a add on 
Required Technical Qualifications<ul><li>12+ years of software engineering experience with 5+ years in principal or staff engineer roles</li><li>5+ years of experience with cloud platforms, preferably Azure with exposure to AWS and OCI</li><li>3+ years of experience with data engineering and lakehouse architectures</li><li>Proven track record of delivering enterprise-scale platforms from inception to production</li><li>Expert-level proficiency in React, Python, and TypeScript</li><li>Deep experience with Databricks, Delta Lake, and Spark</li><li>Strong knowledge of Azure services including AKS, ADLS Gen2, Event Hubs, Azure Functions, and API Management</li><li>Proficiency in designing RESTful APIs and GraphQL services using FastAPI or similar frameworks</li><li>Strong understanding of CI/CD pipelines using Azure DevOps or GitHub Actions</li><li>Experience designing multi-cloud data integration solutions</li><li>Knowledge of FinOps principles and cloud cost management concepts</li><li>Understanding of enterprise security patterns including zero-trust architecture, private endpoints, and managed identities</li><li>Experience with event-driven architectures and streaming data platforms</li><li>Excellent communication skills with ability to present to technical and non-technical stakeholders</li><li>Strong problem-solving and decision-making abilities</li><li>Experience leading distributed engineering teams</li><li>Ability to balance technical excellence with business delivery timelines</li></ul></div>

Principal Full Stack Engineer - Cloud FinOps Platform

D4 Insight

<div>Location: Abu Dhabi 
Experience: 7+ Years
<h3 class="jobSectionHeader">
Role Overview:</h3>

The Azure Platform Engineer will design and operate enterprise Azure environments supporting AI-driven applications and banking platforms.
<h3 class="jobSectionHeader">
Key Responsibilities:</h3>
<ul><li>Build Azure landing zones.</li>
<li>Implement Terraform-based automation.</li>
<li>Integrate Azure OpenAI and AI Search services.</li>
<li>Manage APIM, networking, and cloud operations.</li>
<li>Drive FinOps and cloud optimization initiatives.</li>
</ul><h3 class="jobSectionHeader">Required Skills:</h3>
<ul><li>Azure</li>
<li>Terraform</li>
<li>Azure OpenAI</li>
<li>AI Search</li>
<li>APIM</li>
<li>FinOps</li>
<li>CI/CD</li>
</ul>
 Apply Now: [email protected]</div>

Senior Platform Engineer (Azure Focus)

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>

Role Overview: We are looking for a Senior Platform Engineer to design, build, and scale Azure cloud and hybrid-cloud ecosystems from the ground up for a large Financial Enterprise. You will be responsible for creating a robust foundation for our application teams, with a specific focus on operationalizing AI services, maintaining rigorous security standards, and optimizing cloud spend through FinOps best practices.Key Responsibilities:<ul><li>Greenfield Infrastructure: Architect and deploy production-ready Azure environments from scratch using a landing zone approach.</li><li>AI Orchestration: Integrate and manage Azure AI services (OpenAI, AI Search, Document Intelligence, Content Safety) to support AI-driven application development.</li><li>Infrastructure as Code: Standardize all deployments using Terraform to ensure consistency and modularity.</li><li>API &amp; Connectivity: Manage API lifecycles using Azure APIM and Kong, ensuring secure and performant communication between services.</li><li>FinOps &amp; Monitoring: Proactively manage cloud costs by analyzing SKUs and implementing advanced monitoring/alerting to prevent budget overruns.</li><li>Automation: Design automated GitHub Workflows to enable seamless CI/CD for both infrastructure and application code.</li></ul>Technical Requirements:<ul><li>Cloud: 8+ years experience with Azure Cloud Platform.</li><li>IaC: Expert-level Terraform skills.</li><li>AI Stack: Familiarity with Azure AI Foundry and OpenAI Service.</li><li>Networking: Expert knowledge of Network Architecture (VNETs, Peering, Firewalls, Private Links).</li><li>APIs: Hands-on experience with Azure APIM or Kong.</li></ul>Deployment Architecture: Proven ability to create professional Cloud Architecture Diagrams and provide Solutions Architecture guidance.Pay: AED26,000.00 - AED31,000.00 per monthApplication Question(s):<ul><li>Which tools or approaches have you used for monitoring and alerting (Azure Monitor, Log Analytics, etc.)?</li><li>Have you worked in environments with strict cost governance or quotas?</li><li>Have you created cloud architecture diagrams and presented solutions to stakeholders?</li><li>Describe a complex cloud architecture you designed (include security, scalability, and reliability considerations).</li></ul>Work Location: In person

Lead AI Cloud Platform Engineer (Banking Industry)

Explore 254+ Senior stack engineer in Abu Dhabi this July. Find roles across top companies and apply now to boost your career.

254 senior stack engineer jobs In Abu Dhabi

Senior Full Stack Engineer

Senior AI Engineer

Senior AI Engineer

Principal Full Stack Engineer - Cloud FinOps Platform

Senior Platform Engineer (Azure Focus)

Senior AI Engineer

Lead AI Cloud Platform Engineer (Banking Industry)