civil engineer

planning engineer

electrical engineer

project engineer

qa/qc engineer

ai engineer llm data applications

DICETEK LLC

<div>We are looking for a skilled and motivated AI Engineer to join our team, with a strong focus on developing applications using Large Language Models (LLMs) and related technologies. The ideal candidate will have experience working with modern LLM frameworks, prompt engineering, vector databases, and structured data integration. You will play a key role in designing, building, and deploying intelligent solutions that interact with unstructured and structured data for advanced query and visualization use cases.<h3 class="jobSectionHeader"> 
Key Responsibilities:</h3><ul><li>
Design and develop AI-driven applications leveraging LLMs (OpenAI, Hugging Face models, or local LLMs)</li><li>
Build and optimize workflows using frameworks like LangChain, LlamaIndex, or Haystack</li><li>
Engineer effective prompts for various use cases, ensuring accuracy and consistency</li><li>
Integrate text-to-SQL models to convert natural language queries into database operations</li><li>
Work with vector databases (FAISS, Chroma, Pinecone) for semantic search and retrieval tasks</li><li>
Implement document processing pipelines including PDF ingestion, text chunking, and embedding generation</li><li>
Generate interactive data visualizations using Plotly, Vega-lite, or JSON-based charting tools</li><li>
Collaborate with data engineers, analysts, and product teams to deliver robust AI solutions</li><li>
Maintain clean, modular, and scalable Python code</li></ul><h3 class="jobSectionHeader">
Required Skills:</h3><ul><li>
Strong experience with LLM frameworks (e.g., LangChain, LlamaIndex, Haystack)</li><li>
Familiarity with LLM APIs such as OpenAI, Cohere, or local models via Hugging Face</li><li>
Hands-on experience with prompt engineering and model fine-tuning (preferred)</li><li>
Proficiency in vector databases: FAISS, Pinecone, or Chroma</li><li>
Solid understanding of document processing: text chunking, embedding strategies, and retrieval pipelines</li><li>
Knowledge of text-to-SQL model integration and query optimization</li><li>
Experience with data visualization tools: Plotly, Vega-lite, or equivalent</li><li>
Strong command of SQL and Python</li><li>
Excellent problem-solving skills and ability to work in a fast-paced environment</li></ul></div>

AI Engineer (LLM & Data Applications)

Naffco

<div>Job Summary
We are seeking an AI Engineer to lead the introduction and adoption of agentic AI technologies across the group. You will design, develop, and implement enterprise AI solutions that improve productivity, automation, decision-making, and operational efficiency across industrial, manufacturing, corporate, and support functions.
You will have hands-on experience with modern AI ecosystems, including OpenAI platforms, the Anthropic Claude ecosystem, and Microsoft Copilot Studio. You will bring expertise in enterprise architecture, data lakes, AI agents, LLM integration, and business transformation.
Key Responsibilities<ul><li>
Design and implement enterprise agentic AI solutions across key functions, including manufacturing, finance, HR, procurement, supply chain, sales, customer service, and industrial operations.</li><li>
Develop AI assistants, copilots, autonomous agents, and workflow automation using:<ul><li>
Microsoft Copilot Studio</li><li>
Azure OpenAI Service</li><li>
Anthropic Claude ecosystem</li><li>
LLM APIs and orchestration frameworks</li></ul></li><li>
Lead enterprise data lake and AI-ready platform architecture, integrating ERP, CRM, manufacturing, IoT, and operational systems.</li><li>
Partner with stakeholders to identify, evaluate, prioritize, and implement AI use cases with measurable ROI.</li><li>
Build secure AI frameworks aligned with cybersecurity, governance, compliance, and enterprise standards.</li><li>
Develop Retrieval-Augmented Generation (RAG) solutions for enterprise knowledge bases and operational data sources.</li><li>
Design AI agents for autonomous decision support, workflow execution, predictive analysis, and recommendations.</li><li>
Establish AI governance standards, responsible AI practices, model monitoring, and prompt engineering standards.</li><li>
Collaborate with infrastructure, cloud, cybersecurity, and application teams to deploy scalable AI environments.</li><li>
Run AI innovation workshops, enable users, and build internal AI capabilities.</li><li>
Support executive leadership in defining enterprise AI strategy and the product roadmap.</li></ul>
Technical Skills &amp; Requirements<ul><li>
Bachelor&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related field.</li><li>
3+ years of experience in AI/ML engineering, enterprise automation, or digital transformation.</li><li>
Strong hands-on experience with:<ul><li>
Microsoft Copilot Studio</li><li>
Azure OpenAI Service</li><li>
Anthropic Claude ecosystem</li><li>
LLM integration and prompt engineering</li><li>
AI orchestration and autonomous agents</li></ul></li><li>
Experience with Python, REST APIs, LangChain, Semantic Kernel, vector databases, embeddings, and AI workflow automation.</li><li>
Understanding of data lake architecture, ETL pipelines, structured/unstructured processing, and enterprise integrations.</li><li>
Experience integrating AI solutions with ERP systems such as Oracle ERP, HRMS, manufacturing, CRM, and industrial systems.</li><li>
Familiarity with Microsoft Azure, AWS, or Google Cloud.</li><li>
Knowledge of industrial/manufacturing environments, IoT data, predictive maintenance, and operational analytics is highly preferred.</li><li>
Experience with AI governance, cybersecurity, compliance, and enterprise architecture.</li><li>
Strong communication and stakeholder management skills.</li></ul>
Preferred Skills<ul><li>
Experience in manufacturing or industrial sectors.</li><li>
Experience with AI agents, multi-agent frameworks, and autonomous workflow systems.</li><li>
Knowledge of Power Platform, Power Automate, Fabric, Databricks, and enterprise analytics platforms.</li><li>
AI certifications from Microsoft, OpenAI, or other leading AI platforms are an advantage.</li></ul></div>

AI Engineer – Agentic AI & Enterprise Automation

MultiBank Group

<div>Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
Role Overview
We are seeking a Senior Machine Learning Engineer to join our AI team as a technical owner of ML products and infrastructure. This is a deeply hands-on engineering position for someone who builds and scales production AI systems used by real users in real-time environments. The right candidate operates across the full ML lifecycle &mdash; from model design through deployment, optimization, and ongoing performance in production &mdash; and contributes to the technical direction of the AI platform.
Key Responsibilities<ul><li>
Architect and implement robust ML systems in production environments, ensuring scalability, reliability, and performance from day one</li><li>
Build and deploy supervised, unsupervised, deep learning, and generative AI models into live production environments at scale</li><li>
Own technical design for ML pipelines, feature stores, training infrastructure, and inference systems, driving decisions that balance performance, cost, and maintainability</li><li>
Design and deliver RAG systems, fine-tuning pipelines, prompt engineering frameworks, and evaluation pipelines for production-grade LLM applications</li><li>
Implement and maintain CI/CD for ML, model versioning, monitoring, drift detection, and automated retraining pipelines</li><li>
Continuously optimize model performance, inference latency, cost efficiency, and reliability across live systems</li><li>
Collaborate with product managers, engineers, and data teams to translate business problems into scalable, maintainable AI solutions</li><li>
Mentor junior and mid-level ML engineers, establish best practices, and contribute to technical standards across the team</li><li>
Contribute to strategic decisions around data architecture, AI infrastructure, and cloud platform direction</li><li>
Work with mobile attribution and customer engagement data sources including Adjust, MoEngage, and Firebase for ML use cases such as churn prediction, personalization, and campaign optimization</li></ul>
Requirements<ul><li>
7 to 15 or more years of experience in software engineering, data science, or ML engineering</li><li>
Strong background in product companies, scale-ups, or enterprise AI platforms</li><li>
Proven track record of building production-grade AI systems, not solely notebooks or proof-of-concept work</li><li>
Comfortable owning systems end-to-end from data through model through deployment through monitoring</li><li>
Product-first engineering approach, not research-only profiles</li><li>
Advanced Python engineering skills with strong systems thinking and a focus on production quality</li><li>
Comfortable with fast iteration cycles and deploying models into live environments</li><li>
Ability to work directly and confidently with stakeholders and product owners</li><li>
Fintech or financial services experience is an advantage</li></ul>
Technical Skills
Machine Learning and AI: PyTorch, TensorFlow, XGBoost, LightGBM, Hugging Face (Transformers, Datasets, Diffusers)
LLM and GenAI: OpenAI and Anthropic APIs, LangChain, LlamaIndex; RAG architectures with vector DB and retrieval pipelines; embedding models (OpenAI, Cohere, open-source); Pinecone, Weaviate, Milvus, FAISS; fine-tuning via LoRA and PEFT frameworks; evaluation using RAGAS and custom pipelines
MLOps and Production: Docker, Kubernetes, MLflow, Weights and Biases, Airflow, Dagster, Prefect, GitHub Actions, GitLab CI, Evidently AI, Arize, custom observability stacks
Cloud: AWS (SageMaker, EKS, S3, Lambda), Azure ML, Azure Databricks, GCP
Data Stack: Databricks, Spark, PySpark, Delta Lake, Apache Iceberg, Lakehouse architectures
Why Join Us?<ul><li>
Work with one of the world&rsquo;s leading financial derivatives institutions.</li><li>
Competitive salary plus performance-based incentives.</li><li>
Access to a dynamic, international, and fast-growing environment.</li><li>
Strong opportunities for career progression within a global financial group.</li><li>
Be part of a business committed to innovation, excellence, and long-term growth.</li></ul>
Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.</div>

Senior Machine Learning Engineer

<div>Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
Role Overview
We are seeking a Senior Data Scientist to join our AI and Machine Learning team. The role sits at the intersection of machine learning, computer vision, and large language models, with a focus on delivering production-grade intelligent solutions within a fintech environment. The successful candidate will contribute to AI strategy, lead end-to-end model development, and work closely with cross-functional teams across data engineering, software engineering, and business functions.
Key Responsibilities<ul><li>
Design, develop, and evaluate data-driven algorithms across classification, detection, segmentation, regression, and anomaly detection, applying both classical and deep learning approaches. Rapidly prototype solutions and evaluate their performance against business objectives</li><li>
Prototype and assess LLM-based and multimodal systems for document understanding, knowledge extraction, information retrieval, and workflow automation, including fine-tuning foundation models, building RAG pipelines, and extending models for domain-specific applications</li><li>
Design and implement agentic AI systems including task-oriented agents, workflow orchestrators, tool-using agents, and autonomous reasoning frameworks. Translate complex business workflows into reliable, observable, and maintainable AI-driven pipelines</li><li>
Own the full machine learning lifecycle from data collection, preparation, and cleaning through model training, evaluation, deployment, and ongoing production maintenance. Champion best practices in MLOps, versioning, and reproducibility</li><li>
Contribute to solution architecture and collaborate closely with data engineers, software engineers, and domain experts to integrate AI-enabled products into existing systems</li><li>
Establish robust monitoring frameworks to evaluate AI solution performance post-deployment. Proactively identify data quality issues, model drift, and performance degradation, and drive continuous improvement initiatives</li><li>
Stay current with advances in AI research, mentor junior data scientists, contribute to internal knowledge sharing, and support the broader AI community of practice within the organization</li></ul>
Requirements<ul><li>
5 to 10 years of hands-on experience in classification, detection, and segmentation using both classical and deep learning approaches, applied to real-world, production-grade problems</li><li>
Proven track record of developing, deploying, and scaling end-to-end ML pipelines in industrial or enterprise contexts</li><li>
Hands-on experience building and deploying LLM applications including models such as GPT, Llama, Falcon, and Claude, covering fine-tuning, RAG systems, domain adaptation, and multimodal extensions</li><li>
Experience designing and implementing agentic AI systems including task-oriented agents, workflow orchestrators, or autonomous reasoning frameworks</li><li>
Experience collaborating in cross-functional teams and communicating technical outcomes to non-technical stakeholders</li><li>
Strong foundation in applied mathematics, probability, and statistics underlying modern ML and DL methods</li><li>
Advanced Python programming skills with a focus on clean, production-ready code</li><li>
Deep knowledge of ML algorithms and DL architectures including CNNs, Transformers, Diffusion models, and Graph Neural Networks</li><li>
Proficiency in prompt engineering, evaluation frameworks, and structured output design for LLM-based systems</li><li>
Experience in the fintech sector is a strong advantage</li><li>
Bachelor's, Master's, or PhD in Computer Science, Applied Mathematics, Statistics, or a related field; strong candidates with equivalent industry experience will be considered</li></ul>
Technical Stack<ul><li>
ML Frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost</li><li>
LLM and Agentic Tooling: LangChain, LlamaIndex, Hugging Face, OpenAI and Anthropic APIs, LangGraph, AutoGen, CrewAI</li><li>
MLOps and Development: ClearML, MLflow, Git, Docker, CI/CD pipelines, PyCharm, Jupyter</li></ul>
Why Join Us?<ul><li>
Work with one of the world&rsquo;s leading financial derivatives institutions.</li><li>
Competitive salary plus performance-based incentives.</li><li>
Access to a dynamic, international, and fast-growing environment.</li><li>
Strong opportunities for career progression within a global financial group.</li><li>
Be part of a business committed to innovation, excellence, and long-term growth.</li></ul>
Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.</div>

Senior Data Scientist

Deloitte

<div><div><div>Location</div>
<div>Dubai, Riyadh</div>
</div><div><div>Manager - Senior Manager &ndash; AI &amp; Data
About Deloitte: When you work for us, you commit to a career at one of the largest and most prestigious professional services firms in the world. We have received numerous awards over the last few years, including Best Employer in the Middle East, and Best Consulting Firm, and the Middle East Training &amp; Development Excellence Award.
Our Purpose
Deloitte makes an impact that matters. Every day we challenge ourselves to do what matters most&mdash;for clients, for our people, and for society. We serve clients distinctively, bringing innovative insights, solving complex challenges and unlocking sustainable growth. We inspire our talented professionals to deliver outstanding value to clients, providing an exceptional career experience and an inclusive and collaborative culture. We contribute to society, building confidence and trust in the markets, upholding the integrity of organizations and supporting our communities.
Our shared values guide the way we behave to make a positive, enduring impact:
<ul><li>Lead the way</li>
<li>Serve with integrity</li>
<li>Take care of each other</li>
<li>Foster inclusion</li>
<li>Collaborate for measurable impact</li>
</ul>1. Role Summary
The Senior Manager &ndash; AI &amp; Data will lead the design and delivery of complex AI and GenAI solutions for clients across public and private sectors. The role is techno‑functional, requiring strong hands‑on capability in solution architecture, AI product design, and end‑to‑end delivery of AI initiatives&mdash;from problem framing through production deployment and value realization.
This role is accountable for solution quality, technical design decisions, and delivery outcomes, and it is not just limited to advisory and oversight.
2. Key Responsibilities
AI / GenAI Solutioning &amp; Architecture
<ul><li>Lead end‑to‑end solution design for AI and GenAI applications, including:
</li></ul>o LLM‑based applications (e.g., copilots, document intelligence, chatbots)
o Predictive and prescriptive analytics
o Recommendation and personalization engines
<ul><li>Translate business problems into deployable AI solution architecture, covering:
</li></ul>o Data ingestion and preparation
o Model selection and evaluation
o Application integration and APIs
o Security, scalability, and performance considerations
AI Product &amp; Use Case Development
<ul><li> Define and own AI product roadmaps for client engagements:
</li></ul>o Use case prioritization
o MVP definition and iteration
o Success metrics and adoption measures
<ul><li> Guide teams on build vs. buy vs. partner decisions for models, platforms, and accelerators</li></ul>
<ul><li> Ensure AI solutions are designed for real‑world production use, not PoCs</li></ul>
End‑to‑End AI Delivery (with support of your delivery team):
<ul><li>Lead full AI project lifecycle:
</li><li><ul><li>Discovery and feasibility</li>
<li>Data readiness assessment</li>
<li>Model development and validation</li>
<li>Deployment, monitoring, and iteration</li>
</ul></li><li>Establish practical delivery patterns for:
</li><li><ul><li>Model lifecycle management</li>
<li>Testing and quality assurance</li>
<li>Operational monitoring and retraining</li>
</ul></li><li>Work closely with client technology teams to enable handover and long‑term operability. Guide teams for change management</li>
<li>Flag risks and dependencies on project delivery to raise concerns early during implementation</li>
</ul>Client &amp; Team Leadership
<ul><li>Engage directly with client stakeholders to explain trade‑offs, risks, and design decisions in business terms</li>
<li>Act as the senior technical authority on AI engagements</li>
<li>Review and sign off on solution designs and delivery outputs</li>
<li>Mentor technical teams (data scientists, ML engineers, architects) (Desirable but not mandatory)</li>
</ul>Cloud &amp; Platform Implementation
<ul><li>Architect and solution problem statements on cloud platforms, primarily:
</li><li><ul><li>Azure (Azure AI Services, Azure OpenAI, Azure ML)</li>
<li>AWS (Sagemaker, Bedrock) &ndash; where client context required</li>
<li>GCP (Vertex AI) &ndash; where relevant</li>
<li>This would require to think from an AI product development and deployment perspective rather than POCs for a/b tests</li>
</ul></li><li>Ensure alignment with enterprise architecture and security standards</li>
<li>Apply Data Sovereignty constraints applicable in middle east while reviewing and proposing final solution architecture</li>
</ul>3. Required Experience &amp; Skills
Technical &amp; Functional Expertise
<ul><li>9 &ndash;14+ years of experience in data, analytics, or AI roles with direct delivery accountability</li>
<li>Strong understanding of:
</li><li><ul><li>Machine learning fundamentals and applied AI</li>
<li>Generative AI and LLM architectures</li>
<li>Data engineering concepts supporting AI workloads</li>
</ul></li><li>Proven experience delivering production‑grade AI solutions, not just prototypes and POCs</li>
</ul>AI &amp; GenAI Capabilities
<ul><li>Exposure to:
</li><li><ul><li>LLM orchestration frameworks</li>
<li>Prompt engineering and retrieval‑augmented generation (RAG)</li>
<li>Model evaluation, bias, and performance considerations</li>
</ul></li><li>Practical understanding of AI governance, model risk, and responsible AI considerations</li>
</ul>Consulting &amp; Leadership
<ul><li>Experience working in client‑facing environments</li>
<li>Ability to balance technical depth with commercial and delivery constraints</li>
<li>Strong communication skills for technical and non‑technical audiences</li>
</ul>Cloud &amp; Engineering (desirable)
<ul><li>Experience and exposure to at least one Hyperscaler</li>
<li>Ability to design scalable, secure AI architectures</li></ul></div></div></div>

Manager - Senior Manager | AI & Data | KSA - UAE

sandan AI

<div>Location: Berlin / Remote (DACH time zone) 
Employment Type: Full-time, permanent 
Start Date: Immediate 
Language: Native-level English proficiency (C1-C2 level, German a bonus)

_____________________

ABOUT US

sandan AI is a Berlin-based AI-native startup serving enterprise customers across the DACH region. We are shaping what marketing looks like in an agentic economy &mdash; and building the platform on which this new generation of marketing workflows runs.

Our ambition is to build software the way software should be built in 2026: agentic, iterative, and with AI as an integral part of the engineering workflow.

HOW WE WORK

We use code harnesses such as Claude Code and Codex not as gimmicks, but as a core part of our development process. Our engineers work daily with agentic coding workflows &mdash; from architecture sketches and implementation to refactoring and testing.

People joining us either already work productively with these tools or bring the clear motivation to learn and master them quickly and deeply.
<h2 class="jobSectionHeader">
Tasks</h2>
<ul><li>Develop and maintain our full-stack applications within the modern JavaScript/TypeScript ecosystem</li>
<li>Design and implement scalable backend services using Node.js and Nest.js</li>
<li>Build high-performance frontend solutions with React.js and Next.js</li>
<li>Design and optimize relational databases (PostgreSQL, MySQL, MS SQL)</li>
<li>Containerize and orchestrate services using Docker and Kubernetes</li>
<li>Develop and integrate REST APIs</li>
<li>Build and operate data pipelines, feature stores, and ML workflows for our agentic systems</li>
<li>Develop, train, and evaluate machine learning models for marketing use cases (attribution, targeting, forecasting, anomaly detection)</li>
<li>Implement Retrieval-Augmented Generation (RAG) pipelines (embeddings, vector stores, re-ranking)</li>
<li>Set up and maintain LLM evaluation frameworks, prompt optimization workflows, and systematic quality benchmarks</li>
<li>Apply code harnesses (especially Claude Code and Codex) throughout the daily development process &mdash; from planning and implementation to code review</li>
<li>Collaborate closely with the founding team on the product architecture of agentic systems</li>
</ul><h2 class="jobSectionHeader">Requirements</h2>

Core Technical Competencies (Engineering)
<ul>
<li>Several years of professional experience in full-stack development</li>
<li>Strong knowledge of TypeScript and JavaScript</li>
<li>Confident working with React.js, Next.js, Node.js, and Nest.js</li>
<li>Experience with relational databases (PostgreSQL, MySQL, MS SQL)</li>
<li>Hands-on experience with container technologies (Docker, Kubernetes)</li>
<li>Familiarity with REST API design and Git workflows</li>
</ul>
Data Science &amp; Machine Learning
<ul>
<li>Solid Python skills, including common data/ML stacks (pandas, NumPy, scikit-learn, PyTorch, or TensorFlow)</li>
<li>Experience across the end-to-end lifecycle of ML models: data preparation, feature engineering, training, validation, deployment, and monitoring</li>
<li>Strong understanding of statistical fundamentals (hypothesis testing, regression, classification, time series)</li>
<li>Experience with modern LLM workflows: prompt engineering, RAG, embeddings, vector databases (e.g. Pinecone, Weaviate, pgvector)</li>
<li>Hands-on experience in model evaluation: metrics, benchmarks, A/B testing, and systematic evaluation frameworks</li>
<li>Experience with notebook-based exploration environments (Jupyter, Colab) and transitioning them into production-ready pipelines</li>
<li>Familiarity with MLOps tools (e.g. MLflow, Weights &amp; Biases, DVC) is a plus</li>
</ul>
Code Harnesses
<ul>
<li>Experience with Claude Code and/or Codex is highly appreciated &mdash; otherwise, a strong willingness to actively learn and adopt these tools</li>
</ul>
Personal Qualifications
<ul>
<li>Excellent German (C2) and English skills (minimum C1)</li>
<li>Genuine interest in generative AI and agentic systems</li>
<li>Builder mentality: you deliver production-grade software, not just prototypes</li>
<li>Analytical mindset: you make data-driven decisions and critically evaluate model behavior</li>
</ul>
Nice to have
<ul>
<li>A defining role in an AI-native startup with a strong enterprise focus</li>
<li>Competitive salary and employee stock ownership plan (ESOP)</li>
<li>Fully funded access to all relevant code harnesses, LLM APIs, and developer tools (Claude Max, Codex, GitHub Copilot, etc.)</li>
<li>Compute budget for experiments, model training, and ML workloads</li>
<li>Modern hardware setup (MacBook Pro of your choice)</li>
<li>Flexible working hours and remote work options</li>
<li>Office in Berlin and location in Dubai (DIFC AI Campus)</li>
<li>A steep learning curve in Agentic AI, LLM orchestration, and AI-native engineering</li>
</ul><h2 class="jobSectionHeader">Benefits</h2>
<ul><li>A defining role in an AI-native startup with a strong enterprise focus</li>
<li>Competitive salary and employee stock ownership plan (ESOP)</li>
<li>Fully funded access to all relevant code harnesses, LLM APIs, and developer tools (Claude Max, Codex, GitHub Copilot, etc.)</li>
<li>Compute budget for experiments, model training, and ML workloads</li>
<li>Modern hardware setup (MacBook Pro of your choice)</li>
<li>Flexible working hours and remote work options</li>
<li>Office in Berlin and location in Dubai (DIFC AI Campus)</li>
<li>A steep learning curve in Agentic AI, LLM orchestration, and AI-native engineering</li>
</ul>
We look forward to receiving your application, including your CV and &mdash; if available &mdash; a GitHub or portfolio link.

Please also let us know your earliest possible start date.

Bonus: Tell us in two or three sentences about the most recent ML project you worked on &mdash; and how you currently use Claude Code, Codex, or comparable tools in your workflow.</div>

Senior Full-Stack Developer / AI Engineer / Data Scientist (m/w/d)

Explore 1627+ Ai engineer llm data applications in Dubai this June. Find roles across top companies and apply now to boost your career.

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