ai developer

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

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

Watt Utilities

AI Software EngineerAbout The RoleWe are looking for an AI Software Engineer to help us build the next generation of AI-powered products, features and services.This is not a Machine Learning or Data Science role. Instead, we&rsquo;re looking for an experienced software engineer who has been heavily involved in designing and building production applications using modern AI technologies. You should understand today&rsquo;s AI ecosystem, know how to evaluate emerging AI tools, and be able to identify where AI can create genuine business value.You&rsquo;ll work across our products and platforms, building enterprise-grade web applications while driving the adoption of AI across customer-facing products, internal tools and engineering workflows.Location: On-site in DubaiRequired Technical Skills● Must have 5+ years of professional software development experience● Strong experience with TypeScript, React and Node.js● Deep understanding of Next.js (App Router, Server Actions, Middleware and Routing)● Strong experience with PostgreSQL (or equivalent), including schema design and query optimisation● Must have experience designing and building production AI-powered applications● Strong understanding of Large Language Models (LLMs) and how to integrate them into software products● Experience working with leading AI providers such as OpenAI, Anthropic, Google Gemini or similar● Experience with prompt engineering, structured outputs and tool/function calling● Experience building AI agents, assistants and intelligent automation workflows● Experience implementing Retrieval-Augmented Generation (RAG)● Experience working with embeddings, vector databases and semantic search● Experience building AI applications using modern orchestration frameworks and SDKs (e.g. Vercel AI SDK, LangChain, LangGraph, LlamaIndex or similar)● Familiarity with the Model Context Protocol (MCP) and modern AI tooling ecosystem● Understanding of AI evaluation, latency optimisation, observability and cost optimisation● Experience implementing AI safety, validation and guardrails in production systemsWhat You Will Do● Design, build and ship AI-powered products, features and services● Architect scalable software systems that effectively integrate AI capabilities● Evaluate emerging AI technologies and recommend practical adoption across the business● Build AI agents, assistants and intelligent automation workflows● Develop backend services that support AI-powered experiences● Implement semantic search, RAG pipelines and knowledge retrieval systems where appropriate● Optimise AI applications for quality, performance, reliability and cost● Integrate third-party APIs, AI providers and external services● Collaborate with product managers, designers and stakeholders to solve business problems using AI● Contribute to architecture discussions, code reviews and engineering best practices● Help define engineering standards and reusable patterns for AI development● Stay up to date with the rapidly evolving AI landscape and share knowledge with the wider teamNice To Have● Experience building AI-first SaaS products● Experience with multi-agent architectures● Experience deploying or fine-tuning open-source models● Experience with cloud AI platforms such as AWS Bedrock, Azure AI or Google Vertex AI● Experience with multimodal AI (vision, speech or document understanding)● Experience with AI evaluation frameworks and observability platforms● Contributions to AI open-source projects or personal AI productsAbout You● Passionate about AI and excited by the pace of innovation in the field● You can work autonomously with minimal supervision, taking ownership of tasks from planning to completion● You have a proactive, can-do approach to problem-solving and are willing to tackle unfamiliar challenges● You are comfortable meeting deadlines and handling multiple priorities in a fast-paced environment● You are a team player with a collaborative mindset, open to feedback, and willing to help colleagues● You follow established coding standards and write clean, maintainable, well-documented code● You participate actively in code reviews (giving and receiving feedback)● You take responsibility for testing and quality assurance of your own workJob Type: Full-timePay: AED10,000.00 - AED15,000.00 per monthWork Location: In person

AI Software Engineer

Forsyth Barnes

<div>
 
 We're looking for an experienced AI Workflow &amp; Automation Engineer to join a major enterprise transformation programme.
 
 
 
 
 
 
 Key responsibilities:
 
 
 <ul>
 <li>
 Design and build production n8n workflows
 </li>
 <li>
 Develop AI agents using LLMs, LangChain and RAG
 </li>
 <li>
 Integrate enterprise systems via REST APIs
 </li>
 <li>
 Build AI governance, validation and testing frameworks
 </li>
 <li>
 Support HR automation and digital transformation initiatives
 </li>
 </ul>
 
 
 
 
 
 Key skills:
 
 
 <ul>
 <li>
 n8n
 </li>
 <li>
 LangChain &amp; RAG
 </li>
 <li>
 Azure OpenAI / GPT-4o (or equivalent)
 </li>
 <li>
 REST API integrations
 </li>
 <li>
 AI governance &amp; prompt engineering
 </li>
 </ul>
 
 
 
 
 
 Desirable:
 
 
 <ul>
 <li>
 Oracle EBS HRMS
 </li>
 <li>
 Node.js / NestJS
 </li>
 <li>
 LangSmith / Langfuse
 </li>
 <li>
 pgvector / Vector DBs
 </li>
 <li>
 Redis
 </li>
 <li>
 UAE Government or HR systems experience
 </li>
 </ul>
 
 
 
 
 If you're interested, or know someone who would be a good fit, please get in touch.
 
</div>

N8N Automation Engineer (Ref: 196909)

Alignerr

<div>
 
 About The Role
 
 
 
 What if the code you write could directly shape how the next generation of AI understands and generates software? We're looking for Software Engineers in Dubai to build, evaluate, and improve AI-generated code &mdash; helping train AI systems to think like real developers.
 
 
 You'll write solutions, review AI outputs, and provide the expert-level feedback that makes AI coding assistants smarter, safer, and more reliable. This is hands-on engineering work at the frontier of AI development &mdash; not theoretical, not bureaucratic, and not boring.
 
 
 This is a fully remote, flexible contract role. If you can write clean code and explain your reasoning, we want to hear from you.
 
 
 <ul>
 <li>
 Organization: Alignerr
 </li>
 <li>
 Type: Hourly Contract
 </li>
 <li>
 Location: Remote
 </li>
 <li>
 Commitment: 10&ndash;40 hours/week
 
 
 </li>
 </ul>
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Write, debug, and optimize code across a range of languages, frameworks, and problem domains
 </li>
 <li>
 Review and evaluate AI-generated code for correctness, efficiency, readability, and best practices
 </li>
 <li>
 Identify bugs, logic errors, security issues, and performance bottlenecks in AI outputs
 </li>
 <li>
 Provide structured, detailed feedback explaining why code works &mdash; or doesn't
 </li>
 <li>
 Design challenging coding prompts and edge-case scenarios to stress-test AI capabilities
 </li>
 <li>
 Compare and rank multiple AI-generated solutions based on engineering quality
 </li>
 <li>
 Work independently and asynchronously &mdash; fully on your own schedule
 
 
 </li>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 Proficient in one or more programming languages (Python, JavaScript, Java, C++, Go, TypeScript, or similar)
 </li>
 <li>
 Solid understanding of data structures, algorithms, and software design principles
 </li>
 <li>
 Able to read, write, and reason about code with clarity and precision
 </li>
 <li>
 Strong problem-solving instincts and a systematic debugging approach
 </li>
 <li>
 Clear written communicator &mdash; you can explain technical decisions in plain language
 </li>
 <li>
 Self-motivated and reliable when working independently without supervision
 </li>
 <li>
 Bachelor's degree in Computer Science, Software Engineering, or a related field &mdash; or equivalent practical experience
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience across multiple languages or tech stacks (full-stack, backend, systems, data engineering)
 </li>
 <li>
 Familiarity with AI/ML concepts, LLMs, or prompt engineering
 </li>
 <li>
 Background in code review, technical writing, or mentoring junior developers
 </li>
 <li>
 Experience with cloud platforms, DevOps, or distributed systems
 </li>
 <li>
 Competitive programming, open-source contributions, or side projects that demonstrate your craft
 </li>
 <li>
 Advanced degree in Computer Science or related discipline
 
 
 </li>
 </ul>
 
 Why Join Us
 
 
 
 <ul>
 <li>
 Work on cutting-edge AI projects alongside leading research labs
 </li>
 <li>
 Fully remote and flexible &mdash; set your own hours and work from anywhere
 </li>
 <li>
 Freelance autonomy with intellectually stimulating, high-impact work
 </li>
 <li>
 Directly influence how AI writes, understands, and reasons about code
 </li>
 <li>
 Sharpen your own engineering skills by evaluating diverse problems daily
 </li>
 <li>
 Potential for ongoing work and contract extension as new projects launch
 </li>
 </ul>
</div>

Software Engineer (AI Training)

TALENTMATE

<div>
 
 Overview
 
 
 
 Job Description
 
 
 We empower clients to overcome accounting and financial reporting challenges by delivering innovative technology solutions. As part of our Data &amp; AI team in the AI Hub, you will help drive analytics, decision-making, and innovation, contributing to a more agile and efficient finance function. By fostering outstanding leadership and teamwork, we fulfil our commitment to stakeholders and play a pivotal role in building a better working world for our people, clients, and communities.
 
 
 
 The Opportunity
 
 
 
 We are seeking a Senior AI Software Engineer to join our AI Hub, where we rapidly deliver prototypes, proof-of-concepts (PoCs), and minimum viable products (MVPs), as well as delivering production‑grade solutions that bring AI use cases to life. This role demands expertise across both front-end and back-end development, supporting the creation of dynamic AI-driven products such as GenAI-enabled web applications, use case marketplaces, and diagnostic tools. You will be responsible for designing, building, and optimizing end-to-end solutions, translating business requirements into robust, scalable, secure, and accessible web experiences suitable for enterprise production environments.
 
 
 Core Requirements
 
 
 <ul>
 <li>
 5+ years of professional experience delivering enterprise-grade software solutions across backend and frontend systems.
 </li>
 <li>
 Strong hands-on experience building secure, scalable, and maintainable APIs using Python and Node.js, with frameworks such as FastAPI and Fastify.
 </li>
 <li>
 Solid frontend engineering experience with TypeScript, React, and Next.js, following enterprise UI and accessibility standards.
 </li>
 <li>
 Proven experience containerizing, deploying, and operating applications in production using Docker and Kubernetes, with a strong understanding of reliability and scalability.
 </li>
 <li>
 Experience designing, implementing, and maintaining CI/CD pipelines using Jenkins, GitHub Actions, or Azure DevOps, with automated testing and quality gates.
 </li>
 <li>
 Hands-on experience deploying and operating production workloads on Microsoft Azure, including services such as AKS, Azure Container Apps, Azure Container Registry, and related platform services.
 </li>
 <li>
 Strong understanding and application of software engineering best practices, including SOLID principles, clean architecture, and common enterprise design patterns.
 </li>
 <li>
 Experience working with relational databases such as MS SQL Server and PostgreSQL, including schema design, query optimization, and transactional consistency.
 </li>
 <li>
 Practical experience with vector databases (e.g., Chroma, Milvus, Pinecone) and pgvector, including building and operating Retrieval Augmented Generation (RAG) pipelines in production environments.
 </li>
 <li>
 Ability to collaborate effectively in cross-functional enterprise teams, including product, architecture, security, and cloud/platform teams.
 </li>
 <li>
 Experience working with LLMs and AI platforms, such as Azure OpenAI, OpenAI APIs, or similar enterprise AI services.
 </li>
 <li>
 Familiarity with LLM orchestration frameworks such as LangChain, Semantic Kernel, or equivalent.
 </li>
 <li>
 hands-on experience using AI coding assistants (Claude Code, OpenAI Codex,..etc)
 </li>
 <li>
 Strong documentation skills and experience contributing to architecture decisions, technical standards, and internal best practices.
 </li>
 <li>
 Prior experience mentoring junior engineers or contributing to engineering excellence initiatives.
 
 
 </li>
 </ul>
 Nice to Have
 
 
 <ul>
 <li>
 Exposure to MLOps or AI platform operations, including model lifecycle management, monitoring, and observability.
 </li>
 <li>
 Experience with event-driven or distributed architecture (e.g., message queues, service buses, async processing).
 </li>
 <li>
 Knowledge of observability and monitoring tools (e.g., Azure Monitor, Application Insights, Prometheus, Grafana).
 </li>
 <li>
 Experience working in regulated or compliance-driven environments (e.g., financial services, audit).
 </li>
 <li>
 Familiarity with infrastructure-as-code tools such as Terraform, Bicep, or ARM templates.
 
 
 </li>
 </ul>
 What We Look For
 
 
 We are seeking ambitious builders who excel at transforming ambiguity into impactful digital solutions. You are passionate about AI-driven products, comfortable with rapid prototyping, and motivated by delivering market-relevant, client-centric applications that generate tangible value.
 
 
 What We Offer
 
 
 <ul>
 <li>
 Competitive compensation package, performance-based rewards, and recognition for your contributions.
 </li>
 <li>
 Continuous learning and world-class professional development opportunities.
 </li>
 <li>
 Flexible work arrangements to empower your impact.
 </li>
 <li>
 Coaching, mentorship, and transformative leadership experiences.
 </li>
 <li>
 A diverse, inclusive, and collaborative culture.
 
 
 </li>
 </ul>
 If you meet the above criteria, we encourage you to apply and become part of the exceptional EY experience, where you can shape your future and help us build a better working world.
 
 
 Job Details
 
 
 Role Level: Mid-Level Work Type: Full-Time Country: United Arab Emirates City: Dubai Company Website: http://www.ey.com Job Function: Data Science &amp; AI Company Industry/
 
 
 Sector: Other
 
 
 What We Offer
 
 
 
 About The Company
 
 
 
 Searching, interviewing and hiring are all part of the professional life. The TALENTMATE Portal idea is to fill and help professionals doing one of them by bringing together the requisites under One Roof. Whether you're hunting for your Next Job Opportunity or Looking for Potential Employers, we're here to lend you a Helping Hand.
 
 
 Report
 
 
 Disclaimer: talentmate.com is only a platform to bring jobseekers &amp; employers together. Applicants are advised to research the bonafides of the prospective employer independently. We do NOT endorse any requests for money payments and strictly advice against sharing personal or bank related information. We also recommend you visit Security Advice for more information. If you suspect any fraud or malpractice, email us at abuse@talentmate.com.
</div>

Senior Consultant - AI Software Engineer- AI Hub - Dubai

Boundless

<div>
 
 
 Company Overview
 
 
 
 Our client, a global and rapidly growing financial services group, operates across international markets through a technology-driven, regulated business model. The organisation is investing significantly in Artificial Intelligence, advanced analytics, intelligent automation, and next-generation software engineering capabilities to enhance its platforms, products, internal operations, and customer experience.
 
 
 
 
 
 
 Role Overview
 
 
 
 We are seeking an experienced AI Engineering Lead to establish and drive the organisation&rsquo;s LLM Engineering capability and accelerate AI-powered software development across multiple technology teams. This role will define the standards, architecture, tooling, governance, and development practices required to build secure, scalable, production-ready AI solutions. You will guide engineering teams in adopting modern AI-assisted development workflows, leveraging frontier LLMs, agentic architectures, enterprise RAG systems, and intelligent automation platforms.
 
 
 Working closely with Engineering Managers, Solution Architects, Product Owners, and senior leadership, you will ensure that AI becomes an embedded part of the software development lifecycle. The role combines hands-on technical leadership, architecture oversight, team enablement, and enterprise-wide AI transformation.
 
 
 
 
 
 
 Responsibilities
 
 
 
 
 AI Engineering Leadership &amp; Delivery
 
 
 <ul>
 <li>
 Lead the design, development, and implementation of enterprise-grade LLM applications, AI agents, intelligent automation solutions, and AI-native software products.
 </li>
 <li>
 Guide and mentor engineering teams on AI architecture, prompting strategy, agent design, model selection, code quality, and production deployment.
 </li>
 <li>
 Conduct AI solution design and technical architecture reviews before development begins.
 </li>
 <li>
 Establish engineering standards for secure, scalable, maintainable, and measurable AI implementations.
 </li>
 <li>
 Support teams in adopting AI-first development methodologies while maintaining strong software engineering quality, security, and delivery discipline.
 </li>
 </ul>
 
 
 AI-Assisted Software Engineering
 
 
 <ul>
 <li>
 Champion the use of AI coding and development environments including Claude Code, OpenAI Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, and emerging AI engineering tools.
 </li>
 <li>
 Define enterprise standards for AI-assisted software engineering, developer prompting, code generation, review workflows, and responsible use of AI development tools.
 </li>
 <li>
 Develop reusable prompt libraries, engineering playbooks, technical documentation, and best-practice frameworks.
 </li>
 <li>
 Introduce practical AI-assisted development workflows that improve engineering productivity, code quality, testing, documentation, and delivery speed.
 </li>
 <li>
 Establish methods to measure and improve developer productivity through AI-enabled engineering practices.
 </li>
 </ul>
 
 
 LLM Engineering &amp; Agentic Systems
 
 
 <ul>
 <li>
 Design and optimise production-grade LLM applications using leading models including Claude, OpenAI, Gemini, Mistral, Llama, DeepSeek, and other suitable providers.
 </li>
 <li>
 Build AI agents and multi-agent workflows using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, Haystack, and LlamaIndex.
 </li>
 <li>
 Design and implement enterprise RAG systems using vector databases, knowledge graphs, structured data sources, and internal documentation repositories.
 </li>
 <li>
 Develop scalable MCP servers, tool integrations, API connectors, and secure AI access layers for enterprise systems.
 </li>
 <li>
 Evaluate new LLMs, frameworks, AI platforms, and engineering tools, making recommendations for adoption based on technical fit, security, cost, performance, and business value.
 </li>
 </ul>
 
 
 AI Platform, Architecture &amp; Governance
 
 
 <ul>
 <li>
 Define enterprise AI architecture standards, reference architectures, reusable components, and internal AI platform capabilities.
 </li>
 <li>
 Design secure integrations between LLMs, internal systems, APIs, databases, workflows, and customer-facing applications.
 </li>
 <li>
 Establish guardrails, AI evaluation frameworks, observability standards, model monitoring, prompt testing, and responsible AI practices.
 </li>
 <li>
 Lead technical decision-making around AI infrastructure, deployment patterns, cloud architecture, model hosting, orchestration, and scalability.
 </li>
 <li>
 Support the development of AI governance frameworks covering data privacy, security, access controls, explainability, quality assurance, and risk management.
 </li>
 </ul>
 
 
 Capability Development &amp; Adoption
 
 
 <ul>
 <li>
 Develop an AI Engineering Maturity Model to assess and improve AI adoption across engineering teams.
 </li>
 <li>
 Deliver internal workshops, technical training sessions, and practical enablement programmes for developers, architects, and engineering leaders.
 </li>
 <li>
 Train teams on LLM engineering workflows, AI coding assistants, agentic architectures, RAG implementation, and AI observability practices.
 </li>
 <li>
 Create and maintain internal documentation, coding standards, architecture guidelines, and engineering playbooks.
 </li>
 <li>
 Stay current with emerging AI technologies and continuously identify opportunities to strengthen the organisation&rsquo;s AI engineering capability.
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related technical discipline.
 </li>
 <li>
 At least 7 years of software engineering experience, including strong exposure to software architecture, enterprise applications, APIs, cloud platforms, and modern software delivery practices.
 </li>
 <li>
 At least 3 years of practical experience designing and deploying production LLM applications, AI agents, RAG systems, or intelligent automation solutions.
 </li>
 <li>
 Demonstrated experience leading AI engineering initiatives across multiple engineering teams or business units.
 </li>
 <li>
 Strong hands-on knowledge of LLM application development, prompt engineering, RAG, agentic architectures, MCP, model evaluation, orchestration frameworks, and AI observability.
 </li>
 <li>
 Experience with agent frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, Haystack, or similar technologies.
 </li>
 <li>
 Experience working with vector databases and knowledge systems such as Pinecone, Weaviate, pgvector, Qdrant, Chroma, or similar tools.
 </li>
 <li>
 Strong programming ability in Python and ideally TypeScript, with experience developing APIs using FastAPI or similar frameworks.
 </li>
 <li>
 Strong understanding of REST APIs, Docker, Kubernetes, Git, CI/CD, cloud deployment, and enterprise software integration.
 </li>
 <li>
 Experience with AWS, Microsoft Azure, Google Cloud Platform, or multi-cloud environments.
 </li>
 <li>
 Familiarity with AI observability and evaluation tools such as LangSmith, Helicone, MLflow, Weights &amp; Biases, OpenTelemetry, or similar platforms.
 </li>
 <li>
 Proven ability to mentor engineers, influence technical direction, establish standards, and communicate complex AI concepts to both technical and non-technical stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Preferred Experience
 
 
 <ul>
 <li>
 Building or leading AI Engineering Centres of Excellence.
 </li>
 <li>
 Establishing enterprise AI governance, responsible AI, and AI risk-management frameworks.
 </li>
 <li>
 Driving AI transformation programmes across software engineering organisations.
 </li>
 <li>
 Defining AI coding standards, AI-SDLC frameworks, and AI-assisted development methodologies.
 </li>
 <li>
 Building enterprise LLM platforms, internal AI tools, reusable AI components, or shared AI services.
 </li>
 <li>
 Implementing enterprise RAG, multi-agent architectures, MCP servers, and AI workflow automation.
 </li>
 <li>
 Measuring productivity, quality, adoption, and delivery improvements resulting from AI-enabled software development.
 </li>
 <li>
 Experience within financial services, fintech, trading, payments, regulated technology environments, or large-scale enterprise platforms.
 </li>
 </ul>
 
 
 
 
 
 Key Technology Areas
 
 
 <ul>
 <li>
 Frontier LLMs: Claude, OpenAI GPT models, Gemini, Mistral, Llama, DeepSeek
 </li>
 <li>
 AI Development Tools: Claude Code, Cursor, GitHub Copilot, Gemini CLI, Windsurf, OpenAI Codex, Continue.dev
 </li>
 <li>
 Agent Frameworks: LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, Haystack
 </li>
 <li>
 Automation: n8n, Make, Zapier, Apache Airflow
 </li>
 <li>
 Knowledge Systems: Pinecone, Weaviate, pgvector, Qdrant, Chroma, LlamaIndex
 </li>
 <li>
 Engineering: Python, TypeScript, FastAPI, REST APIs, Docker, Kubernetes, Git, CI/CD
 </li>
 <li>
 Cloud Platforms: AWS, Azure, Google Cloud Platform
 </li>
 <li>
 AI Observability: LangSmith, Helicone, MLflow, Weights &amp; Biases, OpenTelemetry
 </li>
 </ul>
</div>

AI Engineering Lead – LLM Engineering, AI Development & Intelligent Automation

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