project engineer

ai engineer

sales engineer

quality engineer

senior qa/qc engineer

software reliability 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 we expand our footprint across the GCC, we are seeking a talented Site Reliability Engineer (SRE) to join our technical squad and own the ultimate production readiness, resilience, and operational health of our cutting-edge AI solutions.
The Opportunity
If you thrive at the intersection of automated software engineering, high-scale cloud infrastructure, and next-generation AI evaluation, this role was built for you.
As our Site Reliability Engineer, you will bridge application quality, MLOps, and cloud resilience. You will build the automated test suites that validate complex LLM and RAG model outputs, engineer chaos-resilient cloud environments, and establish bulletproof observability frameworks&mdash;ensuring our applications deliver lightning-fast, banking-grade performance under heavy enterprise traffic.
What You&rsquo;ll Do<ul><li>
Implement load testing, fault-injection techniques, and self-healing automation to ensure web/mobile backends and AI microservices easily sustain banking-scale traffic.</li><li>
Build Python-driven, CI/CD-integrated regression test suites that validate application logic, data pipelines, and Infrastructure as Code (IaC) states.</li><li>
Define and track critical Service Level Indicators (SLIs) and Objectives (SLOs). Set up real-time telemetry, dashboards, and proactive alerting to catch performance degradation before users do.</li><li>
Integrate specialized AI evaluation harnesses (e.g., DeepEval, Ragas) into deployment pipelines to benchmark model accuracy, hallucinations, and retrieval performance (RAG).</li><li>
Automate security scans and privacy checks to satisfy strict banking data residency standards, while monitoring compute efficiency to eliminate redundant cloud spend.</li></ul> 
Why Join DeepLight AI?<ul><li> 
You'll be working on High-Impact Systems: Helping to build and deploy real-world, secure AI applications for premier regional enterprise clients.</li><li>
A Culture of Excellence: You'll Collaborate with a world-class team of architects, data engineers, and AI specialists who value craft, accountability, and practical problem-solving.</li><li>
Growth &amp; Impact: You'll take clear ownership of high-visibility platforms, contribute directly to reusable firm IP, and shape how AI is securely deployed across the Middle East.</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 
 
What We&rsquo;re Looking For<ul><li>
High proficiency in Python (mandatory) and Bash scripting, alongside automation test frameworks like PyTest, Selenium, or Robot Framework.</li><li>
Strong hands-on experience with Azure or AWS, focusing on cloud networking, auto-scaling topologies, containerized environments, and serverless reliability.</li><li>
Modern Tooling Command:</li><li><ul><li>
CI/CD &amp; IaC: GitHub Actions, Azure DevOps, and Terraform (reading/validating state).</li><li>
Performance &amp; Load: K6 or JMeter.</li><li>
Observability: Azure Monitor, AWS CloudWatch, Grafana, or Prometheus.</li></ul></li><li>
Solid grasp of prompt engineering, RAG architectures, and model evaluation metrics (ROUGE/BLEU scores, LLM benchmarks, LangSmith/Ragas).</li><li>
Experience operating in financial services, banking, or highly regulated enterprise environments where zero downtime and data privacy are non-negotiable.</li></ul> 

It would also be great if you have: 
<ul><li>
Experience managing production Kubernetes clusters (AKS/EKS), service meshes, and container security scanners.</li><li>
Familiarity with UAE Central Bank regulatory guidelines, NESA security compliance, and data residency mandates.</li><li>
Formal industry credentials such as AWS Certified SysOps Administrator, Microsoft Certified: Azure Administrator Associate, Certified Kubernetes Administrator (CKA), or SRE certifications</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>

Site Reliability Engineer

Halian | Managed Services, Recruitment Agency & Contract Staffing

<div>
 We are seeking an experienced Senior AI Engineer to design, develop, and deploy enterprise-grade AI solutions across complex and large-scale business environments. The ideal candidate will have a strong software engineering background combined with deep expertise in modern AI technologies, Retrieval-Augmented Generation (RAG), LLM integrations, and enterprise system connectivity. This role requires someone who has successfully delivered AI-enabled products within complex organizations, integrating multiple business systems, cloud services, and data platforms while maintaining scalability, security, and performance.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design and develop AI-powered applications using modern LLM frameworks and OpenAI technologies.
 </li>
 <li>
 Build and optimize Retrieval-Augmented Generation (RAG) solutions leveraging structured and unstructured enterprise data.
 </li>
 <li>
 Develop scalable backend services using Java Spring Boot and Python.
 </li>
 <li>
 Integrate OpenAI SDKs and AI services into enterprise applications.
 </li>
 <li>
 Implement observability, tracing, evaluation, and monitoring using Langfuse.
 </li>
 <li>
 Build and maintain APIs and microservices supporting AI workloads.
 </li>
 <li>
 Design and optimize data models within PostgreSQL (PGSQL) environments.
 </li>
 <li>
 Develop frontend and mobile experiences using React Native.
 </li>
 <li>
 Integrate Microsoft ecosystem services including Microsoft Graph API, WorkIQ, and other Microsoft platform capabilities.
 </li>
 <li>
 Deliver integrations with enterprise platforms including ERP systems such as SAP, Oracle, Microsoft Dynamics, or similar solutions.
 </li>
 <li>
 Collaborate with Product Owners, Architects, Security teams, and business stakeholders to define AI use cases and technical solutions.
 </li>
 <li>
 Ensure AI solutions meet enterprise requirements for scalability, security, governance, and reliability.
 
 
 </li>
 </ul>
 Required Skills &amp; Experience
 
 
 <ul>
 <li>
 Minimum 5 years of software engineering experience with proven delivery of enterprise-scale applications.
 </li>
 <li>
 Demonstrated experience working on large-scale, complex projects involving multiple integrations, stakeholders, and high-volume workloads.
 </li>
 <li>
 Strong hands-on experience with Python development.
 </li>
 <li>
 Strong experience with Java Spring Boot and microservices architecture.
 </li>
 <li>
 Practical experience with OpenAI APIs and SDKs.
 </li>
 <li>
 Experience designing and implementing RAG architectures.
 </li>
 <li>
 Hands-on experience with Langfuse or similar LLM observability and monitoring platforms.
 </li>
 <li>
 Strong knowledge of PostgreSQL (PGSQL).
 </li>
 <li>
 Experience building applications using React Native.
 </li>
 <li>
 Experience integrating with Microsoft Graph API and Microsoft productivity ecosystem services.
 </li>
 <li>
 Experience integrating enterprise systems and ERP platforms.
 </li>
 <li>
 Strong understanding of RESTful APIs, authentication, security, and application scalability.
 </li>
 <li>
 Experience working within Agile delivery environments.
 </li>
 <li>
 Excellent problem-solving, communication, and stakeholder management skills.
 </li>
 <li>
 Preferred Qualifications
 </li>
 <li>
 Experience with Azure AI Services, Azure OpenAI, or cloud-native AI architectures.
 </li>
 <li>
 Experience with vector databases and semantic search technologies.
 </li>
 <li>
 Understanding of AI governance, security, and responsible AI principles.
 </li>
 <li>
 Experience deploying AI workloads in production environments.
 </li>
 <li>
 Knowledge of containerization technologies such as Docker and Kubernetes.
 </li>
 <li>
 Experience designing multi-agent or agentic AI workflows.
 
 
 </li>
 </ul>
 AI Engineer in Abu Dhabi, United Arab Emirates
 
 
</div>

AI Engineer (m/f/d)

bankfab

<div><div>Job Description</div>
<div>
 JOB SUMMARY / INTRODUCTION
<ul><li>To lead the engineering, architecture, and run-state ownership of the bank's enterprise AI &amp; Agentic Platform, ensuring it operates as a reliable, secure, observable, and bank-grade production platform supporting agents and AI workloads across the Group.
</li><li>The role is the senior technical authority for platform engineering and architecture across the agentic runtime, model gateway, integration fabric, identity layer, and infrastructure backbone of the platform.
</li><li>It operates in a two-in-a-box model with the existing Platform Product Owner to provide concurrent technical ownership and organizational resilience for the platform, with shared accountability for platform availability, performance, cost, security posture, and architectural evolution.
</li>The role is deeply technical in nature, requiring hands-on engineering depth across distributed systems, agentic protocols, LLM infrastructure, identity and access management, and cloud-native platform engineering. 
<li>
 </li></ul>KEY RESPONSIBILITIES
 Key Accountabilities &mdash; Platform Architecture 
 
<ul><li>Own the end-to-end technical architecture of the AI &amp; Agentic Platform's five-layer stack: Action Gateway, Agent Kernel, Control Plane, Knowledge Foundation, and the Users and Channels layer.
</li><li>Architect and evolve the agentic runtime to natively support the emerging multi-protocol stack: Model Context Protocol (MCP) for agent-to-tool access, Agent-to-Agent (A2A) for inter-agent coordination and task delegation, Agent Communication Protocol (ACP) and equivalent emerging standards, ensuring the platform is interoperable with hyperscaler agent fabrics (Azure AI Foundry agents, AWS Bedrock Agents, Google ADK).
</li><li>Design the platform's agent kernel, including agent lifecycle management, planning and reasoning loops, memory architecture (short-term, long-term, episodic), state management, session affinity, scratchpad persistence, and execution chains.
</li><li>Architect the platform's knowledge foundation, including vector store selection and topology, hybrid retrieval (BM25, dense, graph), embeddings strategy, knowledge graph integration (FIBO, OWL, SHACL, SPARQL), context engineering, and grounding patterns.
</li><li>Design the platform's control plane, including policy-gated execution, Know Your Agent (KYA) enforcement at runtime, agent registries, tool registries, capability discovery, evaluation pipelines, and tracing and lineage at agent and tool granularity.
Key Accountabilities &mdash; Integrations &amp; Model Layer
</li><li>Architect and engineer the platform's LLM gateway and model abstraction layer, providing a unified interface across foundation model providers (Azure AI Foundry, AWS Bedrock, OpenAI, Anthropic, Google Vertex AI, Cohere) with intelligent routing, fallback, retries, prompt and response caching, semantic caching, rate limiting, token accounting, cost attribution, and tenant isolation.
</li><li>Design model serving patterns for managed APIs, dedicated capacity (PTUs / provisioned throughput), and self-hosted open-weight models on GPU infrastructure (vLLM, TGI, Triton, or equivalent), with appropriate trade-offs across cost, latency, sovereignty, and compliance.
</li><li>Lead the integration architecture between the AI Platform and the bank's core estate, including core banking, payments, treasury, credit and risk systems, the enterprise data platform (Azure, Cloudera, Databricks), enterprise APIs, ESB, event streaming (Kafka, Event Hubs), and the data product layer.
 
Design the action gateway as the bank's enforcement boundary for agentic action, including API mediation, contract enforcement, circuit breakers, idempotency guarantees, transactional safety, and audit-grade action logging.
</li><li>Engineer the platform's tool layer and MCP server estate, including tool packaging, versioning, capability advertisement, schema enforcement, and runtime tool discovery across Wholesale, Retail, and Group functions.
Key Accountabilities &mdash; Identity, Security &amp; Governance
</li><li>Architect and own the agent identity and workload identity model for the platform, including non-human identity (NHI) management, agent identity lifecycle, blended user-plus-agent identity for delegated actions, and the identity propagation chain across multi-agent flows.
 
Design the platform's authentication and authorization architecture, including OAuth 2.1 and OIDC flows for agent-to-tool and agent-to-API interactions, just-in-time credential issuance, short-lived token exchange, mTLS for agent-to-agent communication, and integration with the bank's enterprise IAM (Microsoft Entra ID, PAM, secrets management).
</li><li>Implement zero-trust principles across the agentic stack, including least-privilege scoping per agent and per task, real-time policy evaluation, behavioral posture checks, and continuous authorization rather than static service-account-style access.
</li><li>Engineer the platform's runtime governance controls, including KYA enforcement, prompt and output guardrails (PII, PHI, MNPI, prompt injection defense), sensitive action approval flows, and human-in-the-loop escalation patterns.
</li><li>Harden the platform to meet CBUAE, internal model risk, and Group governance requirements, including auditability, lineage, data residency, model risk controls, third-party model governance, and OWASP LLM Top 10 alignment.
</li><li>Key Accountabilities &mdash; Infrastructure &amp; Run-State
</li><li>Lead the platform's cloud and infrastructure architecture across Azure (primary) and AWS, including infrastructure as code (Terraform), networking (private endpoints, peering, egress control), Kubernetes (AKS) and container orchestration, secrets management, and CI/CD pipelines.
</li><li>Own platform Site Reliability Engineering (SRE), including SLO design, error budget management, observability (OpenTelemetry, traces, metrics, logs at agent and tool granularity), incident response, post-mortems, capacity planning, and cost governance for a growing fleet of agents and AI workloads in production.
 
Operate in genuine two-in-a-box with the existing Platform Product Owner, including shared on-call, shared roadmap ownership, and shared accountability for major architectural decisions, regulator conversations, and critical incidents.
</li><li>Drive engineering excellence across the platform team, including testing discipline (unit, integration, evaluation, red-teaming), documentation, infrastructure as code maturity, operational readiness reviews, and technical mentorship of platform engineers.
</li><li>Represent the platform in senior technical forums with Enterprise Architecture, Cyber, Model Risk, Internal Audit, and the Group CTTO's office on architecture and engineering matters.
</li><li>Engage with hyperscale, model provider, and framework vendor technical teams on platform-level integration, performance, sovereignty, and cost optimization.
REQUIREMENTS / QUALIFICATIONS
Technical Expertise
</li><li>Deep, current expertise in agentic AI architecture and the modern multi-protocol stack: Model Context Protocol (MCP), Agent-to-Agent (A2A), Agent Communication Protocol (ACP), and the engineering patterns required to build interoperable agentic systems on top of them at platform scale.
 
Strong hands-on knowledge of agent orchestration frameworks (LangGraph, Google ADK, LlamaIndex, Autogen, CrewAI, OpenAI Agents SDK, or equivalent), planning and reasoning loops, multi-agent coordination patterns, agent memory systems, and evaluation harnesses (RAGAS, OPIK, LangSmith, Promptfoo, or equivalent).
</li><li>Deep technical knowledge of LLM serving and inference architecture, including managed model APIs (Azure AI Foundry, AWS Bedrock, OpenAI, Anthropic, Google Vertex AI), provisioned throughput / PTUs, self-hosted open-weight models, GPU scheduling, vLLM / TGI / Triton, KV-cache management, batching strategies, and the cost-latency-quality trade-offs that drive model selection.
</li><li>Strong working expertise in LLM gateway and AI gateway architecture, including model routing, fallback and retry, prompt and semantic caching, rate limiting, tenant isolation, token accounting, and policy enforcement at the gateway boundary.
</li><li>Deep experience in retrieval and knowledge architecture, including vector databases (pgvector, Azure AI Search, Pinecone, Weaviate, Qdrant, or equivalent), hybrid retrieval, reranking, embeddings model selection, knowledge graphs (FIBO, RDF, OWL, SHACL, Neo4j, Apache Jena), and context engineering at scale.
 
Strong grounding in agent and workload identity, including non-human identity (NHI) governance, agent identity lifecycle, OAuth 2.1, OIDC, SPIFFE / SPIRE-style workload identity, mTLS, just-in-time credentialing, secret-less architectures, and integration with enterprise IAM (Microsoft Entra ID, Azure AD, PAM platforms).
</li><li>Deep proficiency in cloud-native platform engineering on Azure (preferred) and AWS, including Terraform, Kubernetes (AKS / EKS), Helm, service mesh (Istio, Linkerd), API gateways (APIM, Kong, Envoy), private networking, and policy-as-code (OPA, Azure Policy).
 
Strong programming proficiency in at least one of Python, Go, or Java, with active engagement in code reviews, design reviews, and platform-level engineering decisions.
</li><li>Strong Site Reliability Engineering background, including production on-call, incident leadership, post-mortem discipline, SLO and error-budget design, capacity planning, and observability tooling (Open Telemetry, Prometheus, Grafana, Datadog, or equivalent) tuned for non-deterministic AI workloads.
 
Working knowledge of integration patterns relevant to banking platforms, including event-driven architectures (Kafka, Event Hubs), API gateways, ESB, ISO 20022, payment rails, and core banking integration patterns.
</li><li>Strong grounding in security engineering for regulated industries, including OWASP LLM Top 10, prompt injection defence, model supply-chain security, secrets management, network segmentation, data residency, and audit logging.
 
Engineering Leadership &amp; Collaboration
</li><li>Demonstrated ability to operate effectively in a two-in-a-box model with another senior technical owner, including shared accountability, shared on-call, and shared decision-making.
</li><li>Track record of raising engineering standards across a platform team through standards, design reviews, documentation, and direct technical mentorship.
 
Strong written and verbal communication, with the ability to engage credibly with engineers, architects, risk and audit functions, hyperscaler and vendor technical teams, and senior business stakeholders.
 
Minimum Experience
</li><li>10+ years in software and platform engineering, with significant time spent at senior, staff, or principal engineering / architect level.
 
Demonstrated production ownership of at least one platform serving multiple internal or external consumers at enterprise scale, ideally including agentic or LLM workloads.
</li><li>Substantive experience in financial services, banking, or another comparably regulated industry.
 
Demonstrated SRE and on-call experience on a production platform with meaningful availability and operational requirements.
 
Track record of building, integrating, or operating LLM-based or agentic systems in production.
Minimum Qualifications
</li><li>Bachelor's degree in computer science, Software Engineering, Electrical Engineering, or a related technical discipline.
Preferred / Beneficial
</li><li>Master's degree (MSc / MTech / MEng) in Computer Science, Software Engineering, Distributed Systems, or a related discipline preferred.
</li><li>Relevant professional certifications in cloud engineering (Azure Solutions Architect Expert, Azure DevOps Engineer Expert, AWS DevOps Professional, AWS
</li><li>Solutions Architect Professional, Certified Kubernetes Administrator), security (CISSP, CCSP), or SRE considered an advantage.</li></ul></div></div>
 <div><div>Responsibilities</div></div><div></div>
 <div><div>Qualifications</div></div><div></div>
 <div><div>About Us</div>
<div><div>About Us: 
</div><div></div> 
<div>First Abu Dhabi Bank (FAB) is the largest bank in the UAE and one of the world's largest and safest financial institutions. We offer a comprehensive range of personal and private banking services, including credit cards, Islamic banking, investments, loans, and mortgages. Our commitment to excellence and innovation drives us to provide top-tier financial solutions to our clients. 
</div><div></div> 
<div>Life at FAB: 
</div><div></div> 
<div>Working at FAB means being part of a team of talented and passionate individuals with a shared vision to support the ambitions of our stakeholders to &quot;Grow Stronger.&quot; We embrace the needs of our customers across the globe with a sense of responsibility and confidence driven by extensive expertise that can only be delivered by an ambitious world-class organization 
</div><div></div> 
<div>Career Development: 
</div><div></div> 
<div>FAB offers unique career choices, a chance to innovate, craft solutions for the future, and express yourself in a performance-based culture that will unleash the best in you. Whether you are an experienced professional or just starting your career, FAB provides a range of learning and development initiatives to support all employees through training and skill development. 
</div><div></div> 
<div>Our Values: 
</div><div></div> 
<div>At FAB, we place our customers at the core of our activities, live our values each day in every way, celebrate achievements, and empower each other to deliver leading solutions. We have structured plans for the recruitment and career progression of Emirati talent to enable them to make a mark in the financial and banking sector both regionally and globaly that rewards your hard work and dedication. 
</div><div></div> 
<div>Join our team and be part of a journey to shape the future of banking.</div></div></div><div></div>

Senior Engineer, Platform Engineering and Architecture

NorthBay Solutions

<div><h1 class="jobSectionHeader">Full Stack Engineer</h1>
 Location: Abu Dhabi, UAE 
Employment Type: Full-time<h2 class="jobSectionHeader">
 Job Summary</h2>
NorthBay is seeking a Full Stack Engineer with strong expertise in modern front-end and backend technologies, particularly JavaScript/TypeScript, React, Node.js, and Nest.js. The role involves designing, developing, and maintaining scalable full-stack applications for AI-driven platforms, with a strong focus on performance, clean architecture, maintainability, security, and seamless user experience.
The ideal candidate will have hands-on experience building responsive front-end applications and robust backend services using Node.js/Nest.js, developing RESTful APIs, integrating databases and third-party services, and collaborating closely with ML engineers, backend developers, and product/design teams.
Experience working with AI/LLM platforms and AI API integrations is highly desirable.<h2 class="jobSectionHeader">
Key Responsibilities</h2> 
 Design, develop, and maintain scalable full-stack web applications using React, Next.js, TypeScript, Node.js, and Nest.js.<ul><li>Build responsive, accessible, and high-performance front-end applications using modern frameworks and reusable components.</li><li>Develop scalable and secure backend services, APIs, and microservices using Node.js and Nest.js.</li><li>Design and implement RESTful APIs and integrate third-party services and AI APIs.</li><li>Work with databases and data-access layers, ensuring efficient queries, data integrity, and scalability.</li><li>Implement authentication, authorization, security controls, and role-based access where required.</li><li>Collaborate closely with ML engineers, product managers, designers, and other engineering teams to deliver intuitive AI-powered applications.</li><li>Integrate AI/LLM capabilities into web applications, including real-time model outputs and AI-powered workflows.</li><li>Optimize application performance across both front-end and backend layers.</li><li>Build reusable components, services, and design patterns that improve maintainability and development efficiency.</li><li>Participate in architectural discussions, code reviews, technical planning, and engineering best practices.</li><li>Contribute to automated testing, documentation, CI/CD pipelines, and deployment processes.</li><li>Troubleshoot production issues and identify opportunities for improving application reliability, scalability, and performance.</li><li>Mentor junior engineers and contribute to a collaborative engineering culture.</li></ul><h2 class="jobSectionHeader">
Required Skills &amp; Qualifications</h2><ul><li> 
5+ years of full-stack development experience with strong command of JavaScript and TypeScript.</li><li>Strong hands-on experience with React and modern front-end frameworks such as Next.js, Vue.js, or similar.</li><li>Strong backend development experience with Node.js and Nest.js.</li><li>Experience designing and developing RESTful APIs and backend services.</li><li>Strong understanding of backend architecture, API design, authentication, authorization, and security best practices.</li><li>Experience working with relational and/or NoSQL databases such as PostgreSQL, MySQL, MongoDB, or similar.</li></ul> 

VdJnUXaMRL</div>

Full Stack Engineer

Salt

<div>
 
 We are hiring a 𝐀𝐢 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 for an
 
 𝐀𝐛𝐮 𝐃𝐡𝐚𝐛𝐢-𝐛𝐚𝐬𝐞𝐝
 
 opportunity 🇦🇪.
 
 
 This is an exciting opportunity for an early-career software engineer who wants to build real-world AI solutions, work with modern cloud technologies, and grow their experience across Generative AI, application development, and intelligent digital products.
 
 
 
 
 
 
 
 
 
 𝐊𝐞𝐲 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬
 
 
 
 -Support the creation and enhancement of AI-powered digital solutions, working across both backend services and user-facing applications.
 
 
 
 
 
 -Build reliable software components and integrations that can be reused across different products and technology initiatives.
 
 
 
 
 
 -Contribute to cloud-based application development while helping improve performance, scalability, security, and overall user experience.
 
 
 
 
 
 -Collaborate with engineers, product teams, designers, and data specialists to turn ideas and business requirements into working features.
 
 
 
 
 
 -Support software quality through testing, troubleshooting, code reviews, and continuous improvements throughout the development lifecycle.
 
 
 
 
 
 -Explore emerging Ai and software engineering technologies and apply new approaches that improve development efficiency and product capabilities.
 
 
 
 
 
 
 
 
 
 𝐑𝐞𝐪𝐮𝐢𝐫𝐞𝐦𝐞𝐧𝐭𝐬
 
 
 
 -Bachelor&rsquo;s degree in Computer Science, Engineering, Software Engineering, or a related technical discipline.
 
 
 
 
 
 -2+ years of software development experience, ideally with some exposure to Ai-enabled products or digital solutions.
 
 
 
 
 
 -Hands-on knowledge of technologies such as Python, JavaScript/TypeScript, React, or comparable modern development frameworks.
 
 
 
 
 
 -Good understanding of APIs, backend/frontend development concepts, authentication, and secure application development.
 
 
 
 
 
 -Exposure to cloud platforms, container technologies such as Docker, version control, and CI/CD practices; Kubernetes knowledge is an advantage.
 
 
 
 
 
 -Strong interest in AI/ML, Generative AI, and agent-based technologies, with enthusiasm for learning and developing in this space.
 
 
 
 
 
 
 
 
 
 𝐖𝐡𝐚𝐭 𝐌𝐚𝐤𝐞𝐬 𝐓𝐡𝐢𝐬 𝐑𝐨𝐥𝐞 𝐒𝐭𝐫𝐨𝐧𝐠
 
 
 
 A great opportunity to build hands-on experience with modern AI technologies while working alongside multidisciplinary teams on practical, scalable digital solutions.
 
 
 
 
 
 
 
 
 
 𝐇𝐨𝐰 𝐭𝐨 𝐀𝐩𝐩𝐥𝐲
 
 
 
 If you&rsquo;re a software engineer looking to grow your career in AI and work on meaningful technology projects, we&rsquo;d love to hear from you.
 
 
 
 
 
 
 
 
 
 
 ***Only shortlisted candidates will be contacted***
 
 
 
</div>

Artificial Intelligence Engineer (EMIRATI)

DICETEK LLC

<div>Role Overview
The DevOps Engineer owns the AWA platform's deployment, infrastructure-as-code, CI/CD, and operational reliability. You ensure that every AWA component &mdash; from AKS namespaces and KEDA autoscalers to ADLS Gen2 lifecycle policies and Azure Firewall allowlists &mdash; is deployed consistently, tested automatically, and operated reliably within THE BANK's Azure UAE environment. You are the guardian of the AWA infrastructure: nothing is deployed manually; everything is reproducible from code.
Key Responsibilities<ul><li>Infrastructure as code: Own and maintain all AWA Azure infrastructure in Terraform/Bicep: AKS 5-namespace cluster, ADLS Gen2 accounts with WORM policies, Azure AI Foundry APIM configurations, Azure Firewall allowlists, private endpoints, Key Vault, Container Registry, ExpressRoute peering.</li><li>CI/CD pipeline ownership: Design and maintain Azure DevOps pipelines for all AWA components: container image build ACR push Notary v2 signing AKS deployment; Terraform plan policy check apply; Agent Regression Testing gate on every PR.</li><li>AKS operations: Manage the 5-namespace AKS cluster &mdash; namespace isolation, Network Policies, Pod Disruption Budgets, KEDA autoscaling rules based on Kafka consumer lag, OPA Gatekeeper admission policies, Workload Identity bindings for all agent pods.</li><li>Container governance: Manage ACR, enforce Notary v2 image signing, configure vulnerability scanning, maintain the approved-image ConfigMap used by OPA Gatekeeper admission control.</li><li>Secret and certificate management: Own Azure Key Vault configuration &mdash; access policies per managed identity, automatic TLS certificate rotation, secret rotation schedules, audit of all secret access events.</li><li>Monitoring and alerting: Configure Azure Monitor alert rules and Log Analytics KQL queries for SLA breach, error rate spike, pod crash loop, token budget breach, and Kafka consumer lag; maintain PagerDuty escalation paths.</li><li>Security posture: Work with the AI Security Engineer to implement Azure Policy assignments, Defender for Cloud recommendations, Firewall rule reviews, and Private Endpoint configurations; maintain the AWA network topology diagram.</li><li>Disaster recovery: Maintain and test DR procedures: failover to UAE South replica for ADLS Gen2, Azure AI Foundry PTU PAYG DR endpoint routing, Orkes cluster recovery, RTO/RPO validation.</li></ul> 
Required Skills and Experience<h3 class="jobSectionHeader">
Technical &mdash; Essential</h3><ul><li>5+ years DevOps/Platform Engineering; 2+ years on Azure</li><li>Terraform or Bicep &mdash; production IaC, not just templates</li><li>Kubernetes / AKS: namespaces, RBAC, Network Policies, Helm charts, Kustomize</li><li>Azure DevOps or GitHub Actions &mdash; multi-stage pipelines, approvals, environments</li><li>Azure Monitor, Log Analytics, KQL query language</li><li>Container ecosystem: Docker, ACR, image signing, admission control</li><li>Azure networking: VNet, private endpoints, NSGs, Azure Firewall, ExpressRoute concepts</li><li>KEDA (Kubernetes Event-Driven Autoscaling) or equivalent autoscaling experience</li></ul><h3 class="jobSectionHeader"> 
Technical &mdash; Advantageous</h3><ul><li>Azure Key Vault, managed identity, Workload Identity for Kubernetes</li><li>OPA Gatekeeper or Kyverno for Kubernetes policy enforcement</li><li>Kafka / Azure Event Hubs &mdash; consumer group management, lag monitoring</li><li>ADLS Gen2, WORM immutable storage, lifecycle management policies</li><li>Azure AI Foundry / APIM &mdash; token quotas, rate limiting, backend routing configuration</li><li>Security tooling: Defender for Cloud, Sentinel, Notary v2</li></ul>
Skills: Terraform , Kubernetes , Azure DevOps</div>

DevOps Engineers (AIOps) - API and Kubernetes

Smart Artificial intelligence Technology

We are looking for an experienced Arabic Implementation Engineer to join our team and support the successful implementation, configuration, integration, and deployment of our software solutions.-Key Responsibilities - but are not limited to-:<ul><li>Implement and configure software solutions according to customer requirements.</li><li>Work closely with customers, technical teams, developers, and project managers.</li><li>Analyze business and technical requirements and translate them into implementation solutions.</li><li>Support system integration, testing, deployment, and troubleshooting.</li><li>Identify and resolve technical issues during implementation.</li><li>Provide technical support and guidance to customers.</li><li>Prepare implementation documentation, configurations, and technical reports.</li><li>Conduct user training and support customers during go-live.</li></ul>- Requirements:<ul><li>Bachelor&rsquo;s degree in Computer Science, IT, Engineering, or a related field.</li><li>2-3 years experience in software implementation, deployment, integration, or technical support.</li><li>Strong understanding of APIs, databases, SQL, and system integrations.</li><li>Good troubleshooting and problem-solving skills.</li><li>Strong communication and customer-facing skills.</li><li>Fluent Arabic speaker &ndash; mandatory.</li><li>Good English communication skills.</li><li>Experience with cloud platforms, enterprise software, or AI solutions is a plus.</li></ul>Experience:<ul><li>UAE: 3 years (Required)</li></ul>Language:<ul><li>Arabic (Required)</li></ul>Work Location: In person

Implementation Engineer – Arabic Speaker

Explore 41+ Software reliability engineer in Abu Dhabi this August. Find roles across top companies and apply now to boost your career.