ai engineer

Tata Consultancy Services

<div>
 
 
 Job Title
 
 &ndash; AI Engineer
 
 
 
 Company
 
 &ndash; TCS (MEA)
 
 
 
 Location
 
 &ndash; Dubai
 
 
 
 Job type
 
 &ndash; Full time
 
 
 
 
 
 
 About Us:
 
 
 
 Tata Consultancy Services (TCS) is an IT services, consulting and business solutions organization that has been partnering with many of the world&rsquo;s largest businesses in their transformation journeys for over 50 years. TCS offers a consulting-led, cognitive powered, integrated portfolio of business, technology and engineering services and solutions. This is delivered through its unique Location Independent Agile&trade; delivery model, recognized as a benchmark of excellence in software development.
 
 
 A part of the Tata group, India's largest multinational business group, TCS has over 616,171 of the world&rsquo;s best-trained consultants with 157 nationalities in 53 countries. For more information, visit www.tcs.com and follow TCS news at @TCS_News.
 
 
 
 
 
 
 
 Job Description:
 
 
 
 
 
 
 
 
 Key Accountabilities:
 
 
 <ul>
 <li>
 
 AI Solution Design &amp; Development:
 
 </li>
 <li>
 Design, build, and deploy AI-powered applications using Azure AI Services, including Azure OpenAI Service, Azure Machine Learning, Azure Cognitive Services (Speech, Vision, Language), Azure AI Search, Azure Functions, and Azure Databricks.
 </li>
 <li>
 
 LLM Integration &amp; Generative AI:
 
 </li>
 <li>
 Develop and integrate Large Language Model (LLM) solutions using Azure OpenAI endpoints (GPT-4.1, GPT-4o, GPT-4o-mini) routed through FAB's centralized AI Hub gateway for governance, observability, and capacity management. Build enterprise use cases such as knowledge search, document intelligence, content summarization, call analytics, sentiment analysis, and workflow automation.
 </li>
 <li>
 
 Python Engineering &amp; Backend Development:
 
 </li>
 <li>
 Write clean, modular, and production-grade Python code for AI/ML model development, API integrations, data processing pipelines, backend services, and automation workflows using frameworks such as LangChain, LlamaIndex, Semantic Kernel, LangGraph, and FastAPI.
 </li>
 <li>
 
 RAG &amp; Semantic Retrieval:
 
 </li>
 <li>
 Implement Retrieval-Augmented Generation (RAG) pipelines, embeddings, vector search, semantic retrieval architectures, prompt engineering, and evaluation techniques for enterprise knowledge mining and document intelligence.
 </li>
 <li>
 
 Agentic AI Development:
 
 </li>
 <li>
 Design and develop intelligent agentic AI systems capable of planning, reasoning, tool execution, and orchestration across enterprise systems using FAB's GERNAS OS platform and Agent Development Kit (ADK) in a secure and governed manner.
 </li>
 <li>
 
 Model Evaluation &amp; Responsible AI:
 
 </li>
 <li>
 Implement model evaluation metrics for accuracy, hallucination detection, bias, latency, and throughput in alignment with FAB's Responsible AI framework. Ensure AI solutions comply with FAB's security, data privacy, model governance, and regulatory requirements, including controls for accuracy, hallucination, bias, latency, and resilience.
 </li>
 <li>
 
 Deployment &amp; Production Operations:
 
 </li>
 <li>
 Deploy, monitor, and optimize AI solutions in production environments using CI/CD practices, containerization, observability, logging, performance monitoring, and cost optimization techniques.
 </li>
 <li>
 
 Collaboration &amp; Stakeholder Engagement:
 
 </li>
 <li>
 Collaborate with data scientists, platform engineers, DevOps/MLOps engineers, business analysts, and product teams to convert business requirements into scalable AI solutions.
 </li>
 <li>
 
 Innovation &amp; Continuous Learning:
 
 </li>
 <li>
 Continuously evaluate emerging Azure AI, Generative AI, and Agentic AI capabilities and recommend practical adoption opportunities aligned with FAB's AI strategy. Stay abreast of state-of-the-art developments in generative AI and agentic architectures.
 </li>
 </ul>
 
 
 
 
 
 TECHNICAL SKILLS: minimum 3-4 yrs of working experience mandatory
 
 
 
 
 Azure AI Services:
 
 Demonstrated working experience with Microsoft Azure AI Services including Azure OpenAI, Azure Machine Learning, Azure Cognitive Services, Azure AI Search, Azure Functions, and Azure Databricks.
 
 
 
 Python Programming:
 
 Strong proficiency in Python programming, including experience with REST APIs, SDKs, asynchronous processing, data manipulation, backend development, and AI application frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, FastAPI).
 
 
 
 LLM &amp; Generative AI:
 
 Deep understanding of machine learning, statistical modeling, NLP, generative AI principles, LLM application development, prompt engineering, RAG architecture, embeddings, vector databases, semantic search, and model evaluation techniques.
 
 
 
 ML Libraries &amp; Frameworks:
 
 Advanced proficiency in ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and NLP libraries (spaCy, NLTK).
 
 
 
 Vector Databases:
 
 Experience with vector databases including FAISS, Azure AI Search, ChromaDB, and Pinecone.
 
 
 
 DevOps/MLOps:
 
 Hands-on experience with DevOps/MLOps practices and tools such as Git, Docker, Kubernetes, CI/CD pipelines, MLflow, Terraform, Azure Monitor, and Application Insights.
 
 
 
 Cloud Security &amp; Integration:
 
 Understanding of cloud security, identity and access management, data privacy, encryption, logging, monitoring, and secure API integration patterns.
 
 
 
 AI Ethics &amp; Governance:
 
 Awareness of ethical considerations and responsible AI practices, including fairness, accountability, transparency, bias detection, hallucination mitigation, and compliance in AI systems.
 
 
 
 
 
 
 KNOWLEDGE, SKILLS, &amp; EXPERIENCE
 
 
 
 
 
 Minimum Qualifications:
 
 
 
 
 Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or related field; Master's degree is preferred. Microsoft Certified: Azure AI Engineer Associate (AI-102) certification is highly preferred.
 
 
 
 
 Minimum Experience:
 
 
 
 
 3+ years of hands-on experience in designing, developing, and deploying AI/ML or Generative AI solutions in production environments.
 
 
 Mandatory hands-on experience with Microsoft Azure AI Services.
 
 
 Experience working with large-scale datasets and real-time enterprise data.
 
 
 Experience in financial services, banking, risk, compliance, customer service, or regulated enterprise environments is an advantage.
 
 
 
 
 Knowledge and Skills:
 
 
 
 
 
 Business Understanding:
 
 
 
 Strong understanding of business processes and the ability to identify opportunities for AI-driven optimization and automation across banking domains.
 
 
 
 Analytical &amp; Problem-Solving:
 
 
 
 Excellent analytical, problem-solving, debugging, and performance optimization skills with the ability to troubleshoot AI applications in production and translate complex business problems into AI solutions.
 
 
 
 Communication Skills:
 
 
 
 Strong verbal and written communication skills, capable of explaining complex AI concepts to both technical and non-technical stakeholders.
 
 
 
 Collaboration:
 
 
 
 Proven ability to work effectively in cross-functional teams, collaborating with data scientists, platform engineers, DevOps engineers, business analysts, and product teams.
 
 
 
 Responsible AI Mindset:
 
 
 
 Understanding of AI governance, model risk, data privacy, security, and compliance requirements in a regulated banking environment.
 
 
 
 Production Engineering:
 
 
 
 Ability to build, deploy, monitor, and optimize production-grade AI systems with attention to reliability, scalability, cost, and operational excellence.
 
 
 
 Adaptability &amp; Learning:
 
 
 
 Willingness to stay updated on the latest AI technologies, agentic frameworks, and cloud services, and the ability to apply them to solve evolving business challenges.
 
 
 Thank you for your interest in applying for this position with TCS. We will review your application and will get back to you if we are considering your interest in this opportunity.
 
 
 
 
 
 
 Application Deadline: 30- July -2026
 
 
 
 
 
 
 
 Privacy Note:
 
 
 
 https://www.tcs.com/connect-with-tcs/privacy-policy
 
</div>

AI Engineer

Auxo Talent

<div>
 
 Lead AI Engineer
 
 
 Dubai
 
 
 
 
 
 We are supporting a leading enterprise organisation in building a new AI capability.
 
 
 
 
 
 We're looking for a hands-on AI/ML Engineer with experience taking AI solutions from
 
 POC through to production deployment
 
 .
 
 
 
 
 
 This role will focus on building scalable AI applications using GenAI, LLMs, RAG architectures, APIs, and modern AI frameworks.
 
 
 
 
 
 
 Key Requirements
 
 
 <ul>
 <li>
 Strong Python engineering background
 </li>
 <li>
 Experience deploying AI/ML or GenAI solutions into production
 </li>
 <li>
 Hands-on experience with LLMs, RAG, vector databases, and orchestration frameworks (LangChain, LlamaIndex, etc.)
 </li>
 <li>
 Experience with cloud platforms (AWS, Azure, or GCP)
 </li>
 <li>
 Strong understanding of APIs, system design, and software engineering best practices
 </li>
 </ul>
 
 
 
 
 
 Ideal Background
 
 
 
 AI Engineer, ML Engineer, Applied AI Engineer, GenAI Engineer, or Lead AI Engineer with a proven track record delivering production-grade AI systems.
 
</div>

Lead AI Engineer

Salt

<div>
 
 
 Job Title &ndash; Ai Engineer
 
 
 
 
 Salary &ndash; AED 25,000 - 28,500 Per Month
 
 
 
 
 Contract Length &ndash; 12 Months Contract
 
 
 
 
 Location &ndash; Dubai
 
 
 
 
 Start Date - ASAP
 
 
 
 
 
 
 My client is a global data, AI, digital transformation, and consulting company that helps organisations use data and technology to improve business performance, customer experience, and decision-making.
 
 
 
 
 
 
 Role Overview
 
 : The AI Engineer is the primary builder within the AWA AICoE. You will design, build, and test the LangGraph agent graphs, LLM extraction pipelines, prompt management workflows, and MCP tool integrations that power AWA's use cases &mdash; starting with Intelligent Document Processing (IDP) for cheque clearing and expanding across the bank's operations. You will work directly with the dual-layer orchestration stack (Orkes Conductor + LangGraph) and Azure AI Foundry to deliver production-grade agentic systems.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Agent graph development: Design and implement LangGraph agent graphs for Supervisor-Worker orchestration, self-reflection, actor-critic, and HITL interrupt patterns using TypedDict state schemas and conditional edge routing.
 </li>
 <li>
 LLM extraction pipeline: Build and maintain LLM-based entity extraction pipelines using Azure AI Foundry, implementing structured output enforcement, per-field confidence scoring, and Pydantic output validation against Use Case Manifest schemas.
 </li>
 <li>
 Prompt engineering and governance: Author, version, and govern prompts through the AWA Prompt Management System (PMS) using semantic versioning; run prompt sensitivity and correctness testing using the AWA IDP Test Strategy.
 </li>
 <li>
 MCP tool integration: Develop and maintain the five core MCP tool servers (query_structured, retrieve_precedents, query_documents, checkpoint_state, observe) and extend them for new use case requirements.
 </li>
 <li>
 Model evaluation and testing: Execute Band 1 and Band 2 testing (Model Testing, Prompt Testing, Agent Testing, AI Security Testing, Adversarial Testing) per the AWA IDP Test Strategy; maintain the Golden Dataset and Regression Dataset.
 </li>
 <li>
 HITL framework: Implement HITL interrupt() calls at mandatory and dynamic review points in LangGraph graphs; configure Orkes Wait tasks; validate HITL state persistence and checkpoint-based resumption.
 </li>
 <li>
 AI guardrail integration: Integrate Azure AI Content Safety, PII detection and tokenisation, prompt injection shielding, and output sanitisation into agent pipelines at the AWA AI Gateway layer.
 </li>
 <li>
 Cross-field validation rules: Implement business validation rules (amount-words-vs-figures, date validity, MICR format, referential integrity) within LangGraph validation agent nodes.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Required Skills and Experience
 
 
 
 
 Technical &mdash; Essential
 
 
 <ul>
 <li>
 5+ years Python development &mdash; production-grade, not just scripting
 </li>
 <li>
 Hands-on experience with LangGraph, LangChain, or equivalent agentic AI frameworks
 </li>
 <li>
 Practical LLM prompt engineering: structured outputs, few-shot design, output schema enforcement
 </li>
 <li>
 Familiarity with Azure AI Foundry / OpenAI API or equivalent LLM API (Anthropic, Cohere)
 </li>
 <li>
 Understanding of agent design patterns: ReAct, self-reflection, tool use, HITL
 </li>
 <li>
 REST API development and consumption; JSON schema design
 </li>
 <li>
 Git version control; CI/CD pipeline awareness
 </li>
 </ul>
 
 
 
 
 
 Technical &mdash; Advantageous
 
 
 <ul>
 <li>
 Experience with Orkes Conductor, Apache Airflow, or Temporal for workflow orchestration
 </li>
 <li>
 Azure AI Document Intelligence or equivalent OCR platform experience
 </li>
 <li>
 Computer vision model integration (object detection APIs)
 </li>
 <li>
 Knowledge of RAG architectures: chunking, vector indexing, Azure AI Search
 </li>
 <li>
 Azure platform familiarity: AKS, ADLS Gen2, Azure ML, Azure Monitor
 </li>
 <li>
 Pydantic, FastAPI, TypeScript/Node.js
 </li>
 </ul>
 
 
 
 
 
 Domain and Soft Skills
 
 
 <ul>
 <li>
 Genuine intellectual curiosity about AI systems and their failure modes
 </li>
 <li>
 Ability to explain AI behaviour to non-technical Ops and business stakeholders
 </li>
 <li>
 Structured problem-solving and debugging approach for non-deterministic AI systems
 </li>
 <li>
 Banking domain interest &mdash; willingness to deeply understand the business processes being automated
 </li>
 </ul>
 
 
 
 
 Thanks,
 
 
 Ollie
 
 
 
 
</div>

Ai Engineer

Fuse Energy

<div>
 Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. We raised $210M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group and strategic angels like Nico Rosberg, the Co-Founder of Solana and GPs behind Meta, Revolut, Spotify, Uber and more.
 
 
 We're creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers.
 
 
 But we're not stopping there. We're also building the Energy Network: a decentralised platform of smart devices to electrify our homes, shifting usage to off-peak hours and helping balance the grid. This network strengthens grid stability - a critical foundation for scaling AI data centers and other energy-intensive industries.
 
 
 We're now looking to establish a cutting-edge AI team. As an Applied AI Engineer, this position is ideal for someone who possesses the technical expertise of a backend engineer but is specifically interested in applied AI and how it can be used to enhance the energy experience for our customers and our internal operations. You'll be working on a variety of exciting projects, including consumer-focused features like the Energy Co-Pilot and the Speedy Onboarding process (leveraging tools such as VLM/LLM). You will also collaborate across teams to build AI tools that enhance productivity and streamline processes within Fuse.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop and deploy AI-powered features that directly impact consumer experiences, including personalised energy recommendations and seamless onboarding via AI models (e.g. using energy bills for quick setup)
 </li>
 <li>
 Build and optimise internal AI tools that will make the whole company more productive with a focus on automation and enhancing workflows
 </li>
 <li>
 Collaborate with backend engineers and data scientists to integrate AI-driven features into our platforms
 </li>
 <li>
 Collaborate with the trading and operations teams to ensure AI models are aligned with real-time market conditions and energy pricing
 </li>
 <li>
 Improve AI models to optimise trading strategies by anticipating market shifts based on weather and demand forecasts
 </li>
 <li>
 Stay up to date with the latest advancements in applied AI and machine learning and apply them to solve real-world problems within the energy space
 </li>
 <li>
 Monitor the performance of AI tools and models, ensuring they are functioning efficiently and effectively
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Minimum 3 years of engineering experience
 </li>
 <li>
 Proven experience as a Backend Engineer with a strong interest and practical experience in applied AI or machine learning
 </li>
 <li>
 Strong programming skills in Python (or similar languages) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.)
 </li>
 <li>
 Experience working with large-scale models (LLMs/VLMs) and deploying AI-driven solutions into production
 </li>
 <li>
 Solid understanding of cloud technologies, containerisation and building scalable AI applications
 </li>
 <li>
 Ability to integrate AI/ML models into real-world applications, focusing on usability and performance
 </li>
 <li>
 Strong problem-solving skills and a practical approach to implementing AI solutions in a fast-paced environment
 </li>
 <li>
 Experience working with large datasets, particularly in relation to demand and supply forecasting
 
 
 </li>
 </ul>
 
 Bonus
 
 
 
 <ul>
 <li>
 Experience or strong interest in energy markets and trading strategies
 </li>
 <li>
 Understanding of weather forecasting, energy demand patterns, and production modelling
 </li>
 <li>
 Exposure to Natural Language Processing (NLP) or other related fields
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Competitive salary and an equity sign-on bonus
 </li>
 <li>
 Biannual bonus scheme
 </li>
 <li>
 Fully expensed tech to match your needs
 </li>
 <li>
 Paid annual leave
 </li>
 <li>
 Breakfast and dinner allowance for office based employees
 </li>
 </ul>
</div>

Applied AI Engineer

<div>Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. We raised $210M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group and strategic angels like Nico Rosberg, the Co-Founder of Solana and GPs behind Meta, Revolut, Spotify, Uber and more. 
 
We&rsquo;re creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers. 
 
But we&rsquo;re not stopping there. We&rsquo;re also building the Energy Network: a decentralised platform of smart devices to electrify our homes, shifting usage to off-peak hours and helping balance the grid. This network strengthens grid stability - a critical foundation for scaling AI data centers and other energy-intensive industries. 
 
We're now looking to establish a cutting-edge AI team. As an Applied AI Engineer, this position is ideal for someone who possesses the technical expertise of a backend engineer but is specifically interested in applied AI and how it can be used to enhance the energy experience for our customers and our internal operations. You'll be working on a variety of exciting projects, including consumer-focused features like the Energy Co-Pilot and the Speedy Onboarding process (leveraging tools such as VLM/LLM). You will also collaborate across teams to build AI tools that enhance productivity and streamline processes within Fuse. 
 
Responsibilities<ul><li>
Design, develop and deploy AI-powered features that directly impact consumer experiences, including personalised energy recommendations and seamless onboarding via AI models (e.g. using energy bills for quick setup)</li><li>
Build and optimise internal AI tools that will make the whole company more productive with a focus on automation and enhancing workflows</li><li>
Collaborate with backend engineers and data scientists to integrate AI-driven features into our platforms</li><li>
Collaborate with the trading and operations teams to ensure AI models are aligned with real-time market conditions and energy pricing</li><li>
Improve AI models to optimise trading strategies by anticipating market shifts based on weather and demand forecasts</li><li>
Stay up to date with the latest advancements in applied AI and machine learning and apply them to solve real-world problems within the energy space</li>
Monitor the performance of AI tools and models, ensuring they are functioning efficiently and effectively 
<li>
</li></ul> 
 
Requirements 
<ul><li>
Minimum 3 years of engineering experience</li><li>
Proven experience as a Backend Engineer with a strong interest and practical experience in applied AI or machine learning</li><li>
Strong programming skills in Python (or similar languages) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.)</li><li>
Experience working with large-scale models (LLMs/VLMs) and deploying AI-driven solutions into production</li><li>
Solid understanding of cloud technologies, containerisation and building scalable AI applications</li><li>
Ability to integrate AI/ML models into real-world applications, focusing on usability and performance</li><li>
Strong problem-solving skills and a practical approach to implementing AI solutions in a fast-paced environment</li><li>
Experience working with large datasets, particularly in relation to demand and supply forecasting</li></ul>
Bonus<ul><li>
Experience or strong interest in energy markets and trading strategies</li><li>
Understanding of weather forecasting, energy demand patterns, and production modelling</li><li>
Exposure to Natural Language Processing (NLP) or other related fields</li></ul> 

Benefits 
<ul><li>
Competitive salary and an equity sign-on bonus</li><li>
Biannual bonus scheme</li><li>
Fully expensed tech to match your needs</li><li>
Paid annual leave</li><li>
Breakfast and dinner allowance for office based employees</li></ul></div>

Smart Connected Services for Technical Services LLC

About UsTawasol Solution and Services LLC builds AI-powered automation for enterprise systems. We turn complex, real-world data and fragmented platforms into reliable, auditable automation that organizations trust in production.About the RoleWe're looking for a Principal AI Engineer who owns AI systems end to end &mdash; from the architecture on the whiteboard to the code in production. You'll work across a wide range of enterprise problems, combining backend engineering depth with applied LLM expertise. This is a senior builder's role: you set the technical direction, and you ship it, taking systems from first prototype through deployment, operation, and iteration.What You'll Be Working On<ul><li>AI systems, end to end: Architect and implement production AI applications and agentic workflows, owning each one from concept to running system.</li><li>Enterprise integrations: Connect AI systems to enterprise platforms, APIs, and external services through integration layers you design and build.</li><li>Data and document pipelines: Turn messy, real-world unstructured data into production-grade extraction and processing pipelines.</li><li>MLOps and DevOps: Stand up and run the deployment, CI/CD, and monitoring infrastructure behind your systems &mdash; you ship and operate what you build.</li><li>Technical direction: Define the architecture patterns, evaluation strategy, and guardrails for how we build AI, and prove them out in code.</li><li>Production quality: Drive observability, evaluation, latency, and cost across AI workloads.</li></ul>What We're Looking For<ul><li>Strong backend engineering background with production Python; you build systems meant to run, not demos.</li><li>A track record of carrying AI systems solo across the full lifecycle &mdash; design, implementation, deployment, and operation.</li><li>Experience building agentic / LLM-based systems, with a clear point of view on system design and reliability.</li><li>Experience integrating AI with enterprise systems and APIs.</li><li>Practical RAG and document intelligence experience, including the data-quality realities of production.</li><li>Solid MLOps and DevOps foundation: CI/CD, containerization, deployment, monitoring, and infrastructure. Experience with Git workflows and repository management.</li><li>Sound judgment on production LLM concerns: evaluation, latency, cost, and scaling.</li><li>Ability to operate as a technical leader &mdash; owning ambiguous problems end to end and setting direction for others</li></ul>Nice to Have<ul><li>Experience delivering multi-tenant SaaS or enterprise-grade solutions.</li><li>Computer vision or multilingual NLP experience.</li><li>Familiarity with modern cloud and deployment stacks.</li><li>Computer vision experience (e.g., layout/document models, YOLO-family).</li><li>Comfort across the deployment stack (Render, containerized deploys, CI/CD).</li><li>Mobile app development experience</li></ul>Pay: AED15,000.00 - AED18,000.00 per monthApplication Question(s):<ul><li>&quot;Tell us about a multilingual NLP project you have implemented. Which languages were involved, what challenges did you encounter, and which models or techniques did you use to handle multiple languages?&quot;</li><li>Do you have experience on the Mobile App Development?</li><li>Have you personally trained, fine-tuned, or deployed a YOLO-based model or document layout analysis model in a production or commercial environment? Please provide a specific example.</li></ul>Experience:<ul><li>Delivering multi-tenant SaaS or enterprise-grade solutions.: 3 years (Required)</li></ul>Work Location: In person

Principal AI Engineer

Huspy

<div>
 
 The Story So Far: We&rsquo;re Building a Global Brand in Real Estate
 
 
 
 Huspy is one of the leading property technology companies in EMEA.
 
 
 Launched in 2020, we now operate in multiple cities across the UAE and Spain, expanding into Saudi Arabia and 3 more European markets by 2026. Today, we own the largest portion of the UAE mortgage market and are one of the fastest-growing players in every European city we&rsquo;ve entered.
 
 
 We&rsquo;ve raised over $140 million (Series A and Series B) from the world&rsquo;s top investors, including Sequoia Capital, Founders Fund and Balderton Capital, to reshape the homebuying journey through powerful technology and agent-first tools.
 
 
 We&rsquo;ve built a SuperApp that empowers real estate agents and mortgage brokers, bringing cutting‑edge technology to one of the world&rsquo;s most traditional industries. We&rsquo;re transforming how property transactions happen &mdash; faster, smarter, and better for everyone.
 
 
 We&rsquo;re not slowing down. The question is: will you be part of what&rsquo;s next?
 
 
 
 The Main Event: What You&rsquo;ll Drive, Build, and Own
 
 
 
 You will be working closely with Product, Data, and Engineering teams responsible for developing and enhancing AI-powered solutions across our Real Estate Agent Platform and Mortgage Broker Portal. You'll leverage modern machine learning technologies and cloud infrastructure to build intelligent, data-driven products in an innovative and collaborative environment.
 
 
 
 Tech stack:
 
 Python, PostgreSQL, AWS, FastAPI
 
 
 
 Hands-On Engineering:
 
 Contribute to the development, deployment, and optimisation of machine learning models and AI-driven services. Take ownership of key technical deliverables while leading by example in engineering best practices.
 
 
 
 Machine Learning Excellence:
 
 Drive best practices in machine learning development, including data preparation, feature engineering, model training, evaluation, deployment, and monitoring. Ensure solutions are scalable, reliable, and maintainable in production environments.
 
 
 
 Stakeholder Collaboration:
 
 Work closely with Product, Data, Design, and Engineering teams to identify opportunities for AI-driven innovation, translate business requirements into technical solutions, and deliver measurable impact.
 
 
 
 The Perfect Match: What It Takes to Succeed at Huspy
 
 
 
 
 AI/ML Engineering Experience:
 
 Strong technical background in Python and machine learning, with a passion for building intelligent products and solving complex data-driven challenges.
 
 
 
 Product-Focused Mindset:
 
 Ability to work cross-functionally and collaborate with Product, Data, and Engineering teams to deliver impactful AI-powered solutions that enhance customer experiences and business outcomes.
 
 
 
 Technical Expertise:
 
 Experience developing and deploying machine learning models using Python and modern ML frameworks. Strong knowledge of data processing, model lifecycle management, APIs, CI/CD, cloud platforms (AWS preferred), and production-grade software engineering practices. Experience in AI development practices and tools is a must-have.
 
 
 
 Data &amp; Machine Learning Knowledge:
 
 Experience working with structured and unstructured data, feature engineering, model evaluation, experimentation, and performance optimisation. Familiarity with MLOps practices and model monitoring is highly desirable.
 
 
 
 Collaborative Attitude:
 
 Excellent communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders while fostering an inclusive, engaging team environment.
 
 
 
 Work Setup:
 
 Hybrid in Dubai or Madrid, remote anywhere in the EU. Or we offer relocation support to Dubai, if preferred.
 
 
 By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.
 
 
 By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.
</div>

Explore 578+ Ai engineer in Dubai this July. Find roles across top companies and apply now to boost your career.

578 ai engineer jobs In Dubai

AI Engineer

Lead AI Engineer

Ai Engineer

Applied AI Engineer

Applied AI Engineer

Principal AI Engineer

AI Engineer