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Halian | Managed Services, Recruitment Agency & Contract Staffing

<div>
 
 Halian is hiring Forward Deployed AI Engineer
 
 
 in Abu Dhabi.
 
 
 
 
 
 Greetings!
 
 
 
 
 
 Experience required: 8+ Years
 
 
 Duration: 1 year &amp; extendable
 
 
 
 
 
 
 
 
 Technical Skills:
 
 <ul>
 <li>
 8+ years of experience in building and delivering production-grade software solutions.
 </li>
 <li>
 4+ years of hands-on experience with Generative AI, Large Language Models (LLMs), or applied Machine Learning.
 </li>
 <li>
 Minimum 1 year of experience designing and deploying agentic AI solutions.
 </li>
 <li>
 Proven track record of setting technical direction and delivering AI solutions at scale.
 </li>
 <li>
 Hands-on experience or strong working knowledge of Model Context Protocol (MCP) for connecting AI agents with systems, tools, APIs, and data sources.
 </li>
 <li>
 Strong proficiency in Python programming.
 </li>
 <li>
 Hands-on expertise in at least one of the following languages: TypeScript/JavaScript, Java, or C#.
 </li>
 <li>
 Strong understanding of modern engineering practices, including asynchronous programming, FastAPI, Pydantic, CI/CD, testing strategies, source control, logging, and error handling.
 </li>
 <li>
 Hands-on experience with at least one leading agent framework or enterprise AI platform, such as LangGraph, Semantic Kernel, CrewAI, AutoGen, OpenAI Agents SDK, Microsoft Foundry, Amazon Bedrock AgentCore, or Google Vertex AI/Gemini, for building and deploying scalable AI applications.
 </li>
 <li>
 Hands-on experience with vector databases and enterprise search platforms, including Azure AI Search, pgvector, Pinecone, Weaviate, or OpenSearch.
 </li>
 <li>
 Experience integrating enterprise systems through APIs, managed identities, middleware, webhooks, messaging queues, and cloud-native architectures.
 </li>
 <li>
 Practical experience deploying solutions in cloud environments using containers, monitoring, and observability platforms.
 </li>
 <li>
 Strong judgment regarding trade-offs between quality, latency, reliability, security, governance, and cost.
 </li>
 <li>
 Demonstrated curiosity and a passion for understanding complex business and operational challenges.
 </li>
 <li>
 Strong business-first, human-centered approach, recognizing that AI augments people rather than replacing them.
 </li>
 <li>
 Excellent communication skills in English and experience working within diverse, international teams.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 
 
 
 Halian Group
 
 : With over 28 years of experience, we have come to understand that innovation is the only way to provide agile, practical solutions that transform businesses and careers. Our resourcing and smart services help you to realize tomorrow's potential. Discover the amazing things possible when you bring the right people and the right technologies together.
 
</div>

Forward Deployed AI Engineer

BCG X

<div>
 Who We Are
 
 
 Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact.
 
 
 To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures&mdash;and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive.
 
 
 
 We Are BCG X
 
 
 
 We&rsquo;re a diverse team of more than 3,000 tech experts united by a drive to make a difference. Working across industries and disciplines, we combine our experience and expertise to tackle the biggest challenges faced by society today. We go beyond what was once thought possible, creating new and innovative solutions to the world&rsquo;s most complex problems. Leveraging BCG&rsquo;s global network and partnerships with leading organizations, BCG X provides a stable ecosystem for talent to build game-changing businesses, products, and services from the ground up, all while growing their career. Together, we strive to create solutions that will positively impact the lives of millions.
 
 
 What You'll Do
 
 
 Our BCG X teams own the full analytics value-chain end to end: framing new business challenges, designing innovative algorithms, implementing, and deploying scalable solutions, and enabling colleagues and clients to fully embrace AI. Our product offerings span from fully custom-builds to industry specific leading edge AI software solutions.
 
 
 Our AI Software Engineers and Senior AI Software Engineers are part of our rapidly growing engineering team and help to build the next generation of AI solutions. You&rsquo;ll have the chance to partner with clients in a variety of BCG regions and industries, and on key topics like climate change, enabling them to design, build, and deploy new and innovative solutions. Additional responsibilities will include developing and delivering thought leadership in scientific communities and papers as well as leading conferences on behalf of BCG X.
 
 
 We Are Looking For Dedicated Individuals With a Passion For Software Development, Large-scale Data Analytics And Redefining Organizations Into AI Led Innovative Companies. Successful Candidates Possess The Following
 
 
 <ul>
 <li>
 Apply software development practices and standards to develop robust and maintainable software
 </li>
 <li>
 Actively involved in every part of the software development process
 </li>
 <li>
 Experienced at guiding non-technical teams and consultants in and best practices for robust software development
 </li>
 <li>
 Optimize and enhance computational efficiency of algorithms and software design
 </li>
 <li>
 Motivated by a fast-paced, service-oriented environment and interacting directly with clients on new features for future product releases
 </li>
 <li>
 Enjoy collaborating in teams to share software design and solution ideas
 </li>
 <li>
 A natural problem-solver and intellectually curious across a breadth of industries and topics
 
 
 </li>
 </ul>
 What You'll Bring
 
 
 
 Technologies
 
 
 
 Programming Languages: Python
 
 
 #BCGXjob
 
 
 Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws.
 
 
 BCG is an E - Verify Employer. Click here for more information on E-Verify.
</div>

Forward Deployed AI Engineer, United Arab Emirates - BCG X

ARMADA

<div><div>About the Company
<div>
Armada is the hyperscaler for the edge, delivering modular AI infrastructure from first deployment to AI factory with speed, scale and sovereignty. Named one of Fast Company's Most Innovative Companies and to the CNBC Disruptor 50, Armada's solutions are deployed in over 60 countries globally for organizations ranging from energy to defense.

With nearly $500 million in funding to date, Armada is backed by leading investors including Founders Fund, Lux, BlackRock and Microsoft (M12), alongside strategic partnerships with Microsoft, Dell, Palantir, NVIDIA, SpaceX, and Skydio. We are building the infrastructure layer for sovereign and edge AI - rugged, deployable compute for customers that cannot rely on centralized cloud.

Working at Armada means taking ownership, driving autonomy, and delivering impact. You'll tackle challenges that haven't been solved before and help build something transformative from the ground up. What you do here will not only define your career but help further Armada's mission to bridge the digital divide for customers around the world.</div></div><h3 class="jobSectionHeader"> 
About Armada</h3>

Armada delivers sovereign, industrial-grade AI infrastructure designed to operate where traditional cloud and centralized data center models fall short. Our platform includes Atlas as the control plane, Galleon modular edge data centers powered by the Armada Edge Platform, and Leviathan, Armada's AI Factory, which partners with Bridge, our GPU-as-a-Service offering. Together, these capabilities enable enterprises and governments to deploy, operate, and scale AI workloads securely, efficiently, and close to where data is generated.

United Arab Emirates is Armada's operational anchor for the ME region. As we scale, we are intentionally building a team of senior, versatile operators who can both get systems live and own customers long-term. This role is designed for engineers who want full lifecycle ownership, not narrow scope.<h3 class="jobSectionHeader"> 

Role Overview</h3>

The Senior Customer Solutions Engineer, Edge AI is a hybrid role responsible for hands-on deployment execution and ongoing technical account ownership for Armada customers across ME. This role combines the intensity and depth of a Forward Deploy Engineer with the long-term customer ownership of a Technical Account Manager.

In the early phases of customer engagement, this role leads deployments, platform bring-up, and initial workload execution. Once customers are live, the same engineer remains the primary technical owner, driving adoption, operational maturity, and expansion.

This role reports into the Sr. Director of Customer Success &amp; Delivery, EMEA &amp; ANZ and is intentionally designed to avoid split ownership between deployment and post-sale success. Success is measured by speed to production, customer confidence, platform adoption, retention, and expansion. 

<h3 class="jobSectionHeader">
Key Responsibilities</h3>

Deployment execution and platform bring-up
<ul>
<li>Lead end-to-end deployment of Armada platforms including Atlas, Galleon with AEP, and Leviathan AI Factory integrated with Bridge GPU-as-a-Service</li>
<li>Own on-site and in-country deployments across Saudi Arabia and the broader ME region</li>
<li>Own infrastructure bring-up, platform configuration, and production readiness validation</li>
<li>Make real-time technical decisions across hardware, networking, Kubernetes, storage, and GPU layers</li>
</ul>
Technical account ownership and customer success
<ul>
<li>Serve as the primary technical point of contact for assigned customers post go-live</li>
<li>Own the technical success plan, adoption milestones, and operational maturity roadmap</li>
<li>Build trusted, long-term relationships with customer engineering, IT, OT, and security team</li>
<li>Lead technical governance discussions, roadmap planning, and platform optimization conversations</li>
</ul>
Joint Success Plan ownership
<ul>
<li>Build, maintain, and actively drive Joint Success Plans (JSPs) for each assigned customer</li>
<li>Align deployment milestones, platform adoption, and operational maturity to customer business objectives</li>
<li>Use the Joint Success Plan as the primary framework for prioritization, execution, risk management, and value tracking</li>
<li>Regularly review progress against success plans with customer stakeholders and Armada leadership</li>
<li>Ensure JSPs inform deployment sequencing, adoption strategy, roadmap discussions, and expansion planning</li>
<li>Surface risks, dependencies, and blockers early and drive resolution with clear ownership</li>
</ul>
Time-to-value acceleration and adoption
<ul>
<li>Reduce time-to-try and time-to-value by unblocking workloads and accelerating early production use cases</li>
<li>Drive adoption across new workloads, business units, and countries</li>
<li>Identify expansion opportunities including additional Galleon deployments and Leviathan AI Factory capacity through Bridge GPUaaS</li>
</ul>
Operational excellence and reliability
<ul>
<li>Ensure customer environments remain stable, secure, and production-ready</li>
<li>Proactively identify scaling risks, architectural gaps, and technical debt</li>
<li>Coordinate with Product, Engineering, and Support teams to resolve issues efficiently</li>
</ul>
Sovereign data, security, and compliance execution
<ul>
<li>Operate confidently within Saudi and regional sovereign data and security requirements</li>
<li>Support security validation, audits, and governance processes as required by customers</li>
<li>Maintain disciplined access control, documentation, and operational hygiene</li>
</ul>
Field leadership and mentorship
<ul>
<li>Act as a senior technical presence for ND8 customers, setting the bar for execution and professionalism</li>
<li>Mentor junior FDEs, TAMs, and delivery engineers as the region scales</li>
<li>Contribute to deployment standards, runbooks, and repeatable best practices</li>
</ul>
Cross-functional collaboration
<ul>
<li>Partner closely with the Sr. Director of Customer Success &amp; Delivery, EMEA &amp; ANZ on customer priorities and escalations</li>
<li>Work with Sales on expansion planning while maintaining a trusted post-sale posture</li>
<li>Provide structured feedback to Product and Engineering based on real customer usage</li></ul> 

<h3 class="jobSectionHeader">
Qualifications and Experience</h3>
<ul><li>8+ years of experience in infrastructure, platform engineering, SRE, forward-deployed engineering, or technical account roles</li>
<li>Proven ability to own both hands-on delivery and long-term customer technical relationships</li>
<li>Deep technical expertise across Linux, networking, Kubernetes, storage, and GPU-accelerated compute</li>
<li>Strong troubleshooting skills in live, production environments</li>
<li>Experience working directly with customers in regulated, high-stakes settings</li>
<li>Willingness to travel across Saudi Arabia and the broader ME region</li>
<li>Clear, confident communication style suitable for executive and engineering audiences</li></ul> 

<h3 class="jobSectionHeader">
Preferred Experience</h3>
<ul><li>Experience with edge compute, modular data centers, or distributed infrastructure</li>
<li>Familiarity with AI workloads, GPU clusters, and high-performance computing environments</li>
<li>Exposure to sovereign or national-scale customer environments</li>
<li>Experience operating in UAE, Saudi Arabia or across ME</li>
<li>Comfort operating with ambiguity and owning outcomes end to end</li></ul> 

<h3 class="jobSectionHeader">
What Success Looks Like</h3>
<ul><li>Customer environments reach production quickly and operate reliably</li>
<li>The same engineer who deploys the platform remains the trusted technical owner</li>
<li>Adoption expands across sites, workloads, and teams without handoff friction</li>
<li>Customers view Armada as a strategic AI infrastructure partner due to consistent technical ownership</li></ul><div> 
You're a Great Fit if You're
<ul>
<li>A go-getter with a growth mindset. You're intellectually curious, have strong business acumen, and actively seek opportunities to build relevant skills and knowledge</li>
<li>A detail-oriented problem-solver. You can independently gather information, solve problems efficiently, and deliver results with a &quot;get-it-done&quot; attitude</li>
<li>Thrive in a fast-paced environment. You're energized by an entrepreneurial spirit, capable of working quickly, and excited to contribute to a growing company</li>
<li>A collaborative team player. You focus on business success and are motivated by team accomplishment vs personal agenda</li>
<li>Highly organized and results-driven. Strong prioritization skills and a dedicated work ethic are essential for you</li></ul> 


Equal Opportunity Statement

At Armada, we are committed to fostering a work environment where everyone is given equal opportunities to thrive. As an equal opportunity employer, we strictly prohibit discrimination or harassment based on race, color, gender, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other characteristic protected by law. This policy applies to all employment decisions, including hiring, promotions, and compensation. Our hiring is guided by qualifications, merit, and the business needs at the time. 


Unsolicited Resumes and Candidates

Armada does not accept unsolicited resumes or candidate submissions from external agencies or recruiters. All candidates must apply directly through our careers page. Any resumes submitted by agencies without a prior signed agreement will be considered unsolicited and Armada will not be obligated to pay any fees.</div></div>

Senior Customer Solutions Engineer, Edge AI

Janus Digital Global

<div>
 
 About Janus Digital
 
 
 
 
 Janus Digital is the agentic AI platform that runs the world's real assets. Based in the UAE with global operations, our enterprise platform acts as the central operating system for intelligent buildings, and we earn only on the additional value we create.
 
 
 
 
 Buildings account for nearly 40% of global energy consumption and carbon emissions, yet most are still run by fragmented systems that react to problems instead of preventing them. We exist to change that, proving that AI for Good is also good business.
 
 
 
 
 Unlike language models that can guess, our platform is grounded in physics: thermodynamics, pressure dynamics, energy conservation, and fluid mechanics. It builds a live, millimetre-accurate picture of every structure, monitors how energy, water, and air move through every system in real time, anticipates maintenance weeks ahead, and makes thousands of autonomous micro-adjustments around the clock. It calculates; it does not guess.
 
 
 
 The technology is not new, it is battle-hardened: development began in 2009 and has matured through four generations of real-world deployment, built on 15+ years of foundational R&amp;D, 76 granted patents, and over $100M invested. The platform is proven across 10,000+ building datasets in 253 cities, trusted by Fortune Global 500 companies, sovereign wealth funds, and premium hospitality brands, spanning hospitals, airports, malls, theme parks, power grids, and manufacturing. Typical outcomes include around 29% energy savings, 99% equipment-risk detection before failure, and full deployment in 14 days with no phased rollout.
 
 
 
 About This Role
 
 
 
 <ul>
 <li>
 This role sits within the AI Office, the team responsible for designing, building, and running Janus Digital's AI platform and the engineering capability behind it. Reporting to the Head of AI Office, the engineer joins a small, senior group working at the core of how the company applies artificial intelligence across its global operations
 </li>
 <li>
 We are looking for a full-stack AI engineer who combines hands-on software delivery with genuine platform depth&mdash;someone who has built and operated systems to a banking-grade standard and is fluent across modern cloud infrastructure, AWS in particular. That background is central to the work: the AI Office ships production systems the wider organisation depends on, where reliability, security, and clean architecture are not optional. The same instincts that keep banking and financial platforms dependable are exactly what this role demands
 </li>
 <li>
 As part of the AI Office, the engineer will own meaningful parts of the platform end to end&mdash;backend services, user-facing interfaces, identity and access, and the AI agent and integration layers&mdash;and will work alongside existing engineers and the CTO function on cloud deployment and reliability. The objective is a platform engineered to a product standard: secure, scalable, observable, and built to evolve as the company and the field do. This engineer is central to making that real
 
 
 </li>
 </ul>
 
 What you'll do
 
 
 
 <ul>
 <li>
 Build and own the product across the stack: backend services and APIs in Python and TypeScript; frontend interfaces in React (or equivalent) for web dashboards, administrative surfaces, and AI agent interaction layers
 </li>
 <li>
 Build cloud-native software on AWS (primary), and across the wider cloud ecosystem where relevant, that assumes it will run in a managed, containerized cluster environment
 </li>
 <li>
 Design and implement enterprise-grade authentication and authorization: SSO (SAML/OIDC), SCIM provisioning, RBAC, and fine-grained IAM
 </li>
 <li>
 Design the platform for multi-tenancy from the ground up: configuration isolation, provisioning flows, usage metering, and the operational tooling needed to run it reliably at scale
 </li>
 <li>
 Build and deploy production AI agents using MCP and streaming APIs; design multi-model orchestration across Claude, Gemini, and other models as the landscape evolves
 </li>
 <li>
 Contribute to and evolve the memory and knowledge architecture at the core of the platform&mdash;a structured, multi-graph, file-based system underpinning institutional intelligence across the company. This is among the hardest and most consequential engineering problems on the platform
 </li>
 <li>
 Architect the platform as a composition of isolated, independently deployable microservices&mdash;each functional domain (finance tools, marketing stack, knowledge layer, agent runtime) a discrete service with well-defined APIs between them
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 What we're looking for
 
 
 
 <ul>
 <li>
 5+ years in a full-stack software engineering role, with shipped, production systems at scale&mdash;backend and frontend both visible in your GitHub history
 </li>
 <li>
 Direct experience building or operating banking, fintech, or comparable high-reliability, regulated software; you understand first-hand the reliability, security, and compliance bar these environments demand
 </li>
 <li>
 Demonstrable multi-tenant and/or distributed-systems experience: tenant isolation, provisioning flows, and the operational tooling that keeps distributed systems running in production
 </li>
 <li>
 API design for external consumers: versioning, authentication, rate limiting, and documentation standards
 </li>
 <li>
 Security fundamentals: zero-trust principles, data isolation, audit logging, DLP&mdash;security as a design constraint, not a post-launch checkbox
 </li>
 <li>
 Fluent with agentic development tooling&mdash;Claude Code, Codex, and CLI-based AI workflows&mdash;used with discipline and judgment, not as a substitute for engineering thinking
 </li>
 <li>
 Active GitHub profile mandatory&mdash;applications without a demonstrable commit history will not be considered
 
 
 </li>
 </ul>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Broad, hands-on cloud experience: AWS (primary), with working knowledge across the wider cloud ecosystem (GCP/Azure). You architect cloud-native systems, not just deploy to a single VM
 </li>
 <li>
 Containerization and cloud-native deployment in production: Docker and Kubernetes; you write software that assumes it will run in a managed cluster environment
 </li>
 <li>
 Strong Python and TypeScript; React or an equivalent modern frontend framework; genuine comfort moving between layers of the stack
 </li>
 <li>
 Enterprise identity and access management implemented in production&mdash;SSO (SAML/OIDC), SCIM, RBAC, Okta or Azure AD&mdash;not just read about
 </li>
 <li>
 AI/LLM integration: MCP server development, function calling, streaming APIs, and multi-model orchestration
 </li>
 <li>
 Experience with core banking, payments, or other regulated financial systems (transaction integrity, settlement, KYC/AML data flows, and similar)
 </li>
 <li>
 Vertex AI / Google AI Studio / Claude API / Gemini Enterprise
 </li>
 <li>
 Slack Apps (Bolt Framework, Block Kit) and Google Workspace integrations
 </li>
 <li>
 Agent memory patterns, structured knowledge graphs, or evolving AI context-management architectures
 </li>
 <li>
 Regional compliance experience (GDPR, Singapore PDPA, UAE data protection frameworks)
 </li>
 <li>
 Familiarity with Terraform or equivalent IaC tooling (ownership sits with the infrastructure team, but fluency helps)
 </li>
 <li>
 Go or Rust for performance-critical components
 </li>
 <li>
 Experience taking an internal platform or product through significant scale or its first external users
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Competitive compensation with performance-based incentives tied to delivery quality and client outcomes
 </li>
 <li>
 A specialized domain-expert role at the absolute frontier of Agentic AI and autonomous building intelligence
 </li>
 <li>
 Hands-on engagement with prestigious, diverse real estate portfolios (commercial offices, hotels, malls, and mixed-use developments)
 </li>
 <li>
 Direct collaboration with our global Head of AI team
 </li>
 <li>
 Clear career progression paths into senior consulting or regional delivery leadership roles
 </li>
 <li>
 Sponsorship and support for professional development, including certifications in building services and energy management
 </li>
 </ul>
</div>

AI Software Engineer

The Emirates Group

<div><h5 class="jobSectionHeader">Job Purpose
</h5>Join the Emirates Group Analytics Centre of Excellence (ACoE), where data, AI and innovation power decisions across one of the world's most recognised aviation and travel brands. 
 
As a Data Scientist/AI Engineer , you will solve complex business challenges using machine learning, advanced analytics, GenAI and Agentic AI. Working across commercial, operational and customer domains, you will transform vast amounts of data into actionable insights, intelligent products and measurable business outcomes.
This is an opportunity to work on real-world, large-scale problems while helping shape the future of AI and data-driven decision making at Emirates Group. 
 
In this role, you will:
<ul><li>Develop and deploy machine learning, Agentic AI and analytics solutions that drive measurable business impact.
</li><li>Analyse large structured, semi-structured and unstructured datasets to uncover insights and opportunities.
</li><li>Build predictive, prescriptive and optimisation models to solve business challenges across the Emirates Group.
</li><li>Partner with stakeholders to translate complex business questions into scalable data science solutions.
</li><li>Create visualisations, dashboards and analytical tools that support decision-making.
</li><li>Contribute to the development of reusable libraries, frameworks and production-ready data science assets.
</li><li>Apply experimentation techniques including A/B testing, segmentation and customer analytics.
</li><li>Collaborate with engineers, analysts and product teams in an agile delivery environment.
</li>Support the development and deployment of AI-powered products and intelligent automation capabilities. 
<li>
</li></ul> 
<h5 class="jobSectionHeader">Qualification
</h5>To be considered for this role, you must meet the below requirements:
Qualifications
<ul><li>MSc or PhD in Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Operations Research, Computer Science, Economics or a related quantitative discipline.
</li></ul>Experience
<ul><li>2-4+ years of experience delivering advanced analytics, machine learning or AI solutions in a commercial environment.
</li></ul>Knowledge &amp; Skills
<ul><li>Strong hands-on experience across the modern Data Science ecosystem.
</li><li>Experience developing and deploying Machine Learning, GenAI, LLM and Agentic AI solutions.
</li><li>Experience with AI Engineering practices including model deployment, monitoring, evaluation, prompt and context engineering and scalable AI application development.
</li><li>Proficiency in Python, SQL and modern analytical toolsets.
</li><li>Experience with Sparkor distributed data processing technologies.
</li><li>Experience with Git, Docker, CI/CD and MLOps workflows.
</li><li>Experience building reusable libraries, APIs or production-grade data science solutions.
</li><li>Strong problem-solving mindset with the ability to communicate technical concepts to non-technical audiences.
</li><li>Experience delivering solutions in complex, fast-paced environments.
</li></ul>Preferred Experience
<ul><li>Experience building and deploying AI applications using LLM orchestration frameworks (LangGraph, LangChain, Semantic Kernel or equivalent).
</li><li>Experience with Retrieval Augmented Generation (RAG), vector databases, AI agents and multi-agent systems.
</li><li>Experience evaluating, monitoring and governing production AI systems.
</li><li>Understanding of cloud-native AI platforms and modern AI engineering best practices.
</li></ul><h5 class="jobSectionHeader">Salary &amp; benefits
</h5>Join us in Dubai and enjoy an attractive tax-free salary, industry-leading travel benefits, and access to one of the most exciting AI and data environments in the region. Alongside discounted flights and hotel stays worldwide, you'll have the opportunity to work on high-impact projects at global scale while advancing your career with Emirates Group.</div>

Data Scientist/AI Engineer

Derq

<div>Derq is an MIT spinoff building AI-powered traffic safety and smart infrastructure. We&rsquo;re a team of passionate innovators, leveraging the latest in AI and technology to transform the future of mobility. Our platform enhances road safety and traffic management by turning real-time data into actionable insights for cities and road operators. Our patented technology collects and analyzes data from connected sensors like cameras, radar, and traffic signal controllers to help predict and prevent road incidents. We deploy edge and cloud solutions that make intersections and highways safer and smarter.
Role Overview
We are looking for a Full-Stack Software Engineer to join our growing engineering team. In this role, you will work across frontend, backend, and cloud infrastructure to build scalable, high-availability products and services powering intelligent transportation systems.
You will contribute to customer-facing applications, backend APIs, cloud-native services, and data pipelines that support real-time analytics, complex workflows, and production-critical operations. This role is ideal for someone who enjoys owning features end-to-end, building for scale, and working in a fast-moving environment where engineering has direct impact on real-world deployments.
Key Responsibilities<ul><li>
Design, develop, and maintain full-stack applications across frontend and backend systems</li><li>
Build responsive and scalable frontend applications using React (Remix), TypeScript, and Vue.js</li><li>
Develop backend services and APIs using NestJS and modern microservice architectures</li><li>
Design and optimize integrations with relational databases and data platforms</li><li>
Build and maintain event-driven cloud pipelines using AWS services such as S3, SQS, Lambda, Cognito, and API Gateway</li><li>
Develop ETL and data transformation workflows using Python</li><li>
Deploy and manage containerized applications using Docker and Kubernetes (EKS)</li><li>
Contribute to CI/CD pipelines using GitHub Actions and ArgoCD</li><li>
Collaborate with product, engineering, and deployment teams to deliver reliable production-ready solutions</li><li>
Troubleshoot production issues, improve system performance, and support scalability initiatives</li><li>
Participate in technical discussions, architecture reviews, and engineering best practices</li></ul> 

Requirements 
<ul><li>
7+ years of experience in Full‑Stack engineering, working across frontend, backend, and production environments</li><li>
Experience building scalable, high-availability platforms that support large user volumes, complex workflows, and production-critical operations</li></ul><ul><li>
Strong frontend experience with React (Remix), TypeScript, and Vue.js (Vue 2 &ndash; legacy)</li><li>
Backend experience using NestJS and building APIs / microservices</li><li>
Solid experience with relational databases (RDBMS) and familiarity with MongoDB and Amazon Redshift</li><li>
Hands‑on experience with public cloud platforms (AWS preferred) and services such as S3, SQS, Lambda, Cognito, and API Gateway</li><li>
Experience building event‑driven pipelines (S3 SQS Lambda), using Python for ETL and data transformation</li><li>
Experience with CI/CD pipelines (GitHub Actions, ArgoCD) and containerized deployments using Docker and Kubernetes (EKS)</li><li>
Comfortable working independently, taking ownership, and operating in a fast‑moving environment</li></ul></div>

Senior Full-Stack Engineer (Scalable Systems)

noon

<div>
 
 
 About noon
 
 
 
 noon, the region's leading consumer commerce platform. On December 12th, 2017, noon
 
 
 launched its consumer platform in Saudi Arabia and the UAE, expanding to Egypt in February
 
 
 2019. The noon ecosystem of services now marketplaces for food delivery, quick commerce,
 
 
 fintech, and fashion. noon is a work in progress; we&rsquo;re six years in, but only 5% done.
 
 
 noon&rsquo;s mission: Ring every doorbell, every day.
 
 
 
 
 
 
 Who are we?
 
 
 
 Everyday Labs is noon&rsquo;s innovation engine &mdash; a place built to imagine, build, and scale new ideas that create real value for users, for noon, and for the world. Our mission is simple: turn imagination into measurable impact. We explore new technologies, test new business models, and launch products that push noon&rsquo;s ecosystem forward with speed, clarity, and purpose.
 
 
 If you want to build models, ML pipelines and AI that become the foundation for future noon businesses, this is where you belong.
 
 
 
 
 
 
 About the role:
 
 
 
 As a Staff Machine Learning Engineer at Everyday Labs, you will architect and deliver the intelligence that powers our next generation of products, experiments, and ventures. You will work at the intersection of applied machine learning, experimentation, and scalable engineering &mdash; building models and ML infrastructure that can go from idea to deployed value with exceptional velocity and rigor.
 
 
 
 
 
 This is a highly technical, high-ownership role where you will influence technical strategy, hire and mentor engineers, and help shape the culture and systems that allow ML ideas to become high-impact reality.
 
 
 
 
 
 
 What you'll do:
 
 
 
 
 
 
 
 Machine Learning: Turning Ideas into Value
 
 
 
 &bull; Design, train, and deploy ML models that deliver measurable impact across multiple aspects of noon&rsquo;s vast e-commerce footprint.
 
 
 &bull; Translate ambiguous or zero-to-one problems into clear hypotheses, measurable signals, and verifiable ML solutions.
 
 
 &bull; Collaboration with product, engineering and business leaders to define value metrics and success thresholds early and rigorously.
 
 
 
 
 
 
 Production ML Systems &amp; Pipelines:
 
 
 
 &bull; Architect reliable training, validation, and deployment pipelines using modern MLOps practices.
 
 
 &bull; Build and maintain feature stores, automated retraining systems, online inference services, and monitoring frameworks.
 
 
 &bull; Ensure systems meet high bars for observability, reliability, and performance &mdash; excellence in execution is part of our signature.
 
 
 
 
 
 
 Technical Leadership &amp; Cross-Team Ownership:
 
 
 
 &bull; Hire and mentor ML and software engineers across Labs in traditional ML, generative AI technologies.
 
 
 &bull; Contribute to cross-initiative architecture, documentation, and open knowledge sharing.
 
 
 &bull; Work noon partners and stakeholders to apply ML where it can unlock disproportionate impact.
 
 
 
 
 
 
 What you'll need:
 
 
 
 &bull; 6+ years of experience in applied ML engineering
 
 
 &bull; Bachelor's degree in Computer Science, Engineering, or a related technical field, master&rsquo;s or PhD is a plus but not required.
 
 
 &bull; Strong proficiency with Python, modern ML frameworks (PyTorch, TensorFlow, Scikit-learn, XGBoost), and model lifecycle best practices.
 
 
 &bull; Proven experience deploying ML models into real-world systems with CI/CD and automated monitoring.
 
 
 &bull; Strong SQL and data engineering fundamentals, including building scalable data pipelines (Airflow or similar).
 
 
 &bull; Experience with cloud platforms (AWS, GCP, Azure). GCP is a plus.
 
 
 &bull; Experience with generative AI, LLMs, or NLP systems is a strong bonus.
 
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Staff Machine Learning Engineer

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