data platform engineer

Group AMANA

<div>
 
 Amana is seeking an experienced Data Platform Lead with deep expertise in Databricks, the Microsoft Azure ecosystem, and modern lakehouse architectures. The ideal candidate will play a central role in Amana's ongoing platform refresh, moving workloads from Synapse Analytics to a Databricks lakehouse with Unity Catalog, and building the technical foundation that powers analytics, AI, and governance across the enterprise. This role sits within Amana's Data Science, Governance &amp; AI Centre of Excellence, working alongside architects, engineers, analysts, data scientists, and AI engineers, with future growth opportunities into senior platform leadership.
 
 
 
 
 
 
 Why This Role Matters
 
 
 
 Amana operates across capital-intensive sectors where data reliability, cost discipline, and speed of insight are business-critical. The enterprise data platform is the backbone of every downstream analytics, AI, and governance initiative &mdash; from ERP-integrated reporting and predictive models to Agentic AI and Copilot rollouts across the group.
 
 
 You will be at the technical centre of this transformation, designing, building, and hardening the lakehouse that the rest of the function depends on.
 
 
 
 
 
 
 Core Responsibilities
 
 
 
 
 Lakehouse Architecture &amp; Delivery
 
 
 <ul>
 <li>
 Design and deliver end-to-end Databricks lakehouse components &mdash; ingestion, transformation, semantic layer, and serving.
 </li>
 <li>
 Set and enforce Delta Lake and medallion architecture standards across bronze, silver, and gold layers.
 </li>
 <li>
 Lead the technical execution of the Synapse Analytics to Databricks migration, including parallel run, cutover, and decommissioning.
 </li>
 <li>
 Contribute to and sign off on reference designs, integration patterns, and architecture decision records.
 </li>
 </ul>
 
 
 
 
 
 Data Engineering &amp; Integration
 
 
 <ul>
 <li>
 Build and maintain robust ingestion and transformation pipelines from Amana's core enterprise systems: Oracle Fusion (Finance, HCM, P2P, CRM), Hyperion, CMiC, project and operations systems, SharePoint, and Power Platform.
 </li>
 <li>
 Apply strong CI/CD, DataOps, and infrastructure-as-code practices using Git, Azure DevOps, and Terraform or Bicep.
 </li>
 <li>
 Ensure platform reliability through monitoring, alerting, and structured incident response.
 </li>
 </ul>
 
 
 
 
 
 AI/ML &amp; Analytics Enablement
 
 
 <ul>
 <li>
 Build and operate feature store, MLOps, and LLMOps foundations on Databricks.
 </li>
 <li>
 Enable production-grade RAG, agent, and Copilot patterns in partnership with the Data Scientist and AI Engineer.
 </li>
 <li>
 Deliver Power BI semantic models, certified datasets, and self-service guardrails supporting the Amana Digital Academy and enterprise adoption.
 </li>
 </ul>
 
 
 
 
 
 Data Governance &amp; Trustworthy Data
 
 
 <ul>
 <li>
 Implement lineage, cataloguing, access control, data quality, and PDPL controls inside the platform using Unity Catalog and Microsoft Purview.
 </li>
 <li>
 Partner with the Data Governance Office to translate live policies into enforceable platform controls.
 </li>
 <li>
 Support regulatory, ethical, and internal compliance obligations across the data estate.
 </li>
 </ul>
 
 
 
 
 
 Cloud &amp; Cost Discipline
 
 
 <ul>
 <li>
 Own FinOps hygiene on the platform: cluster policies, workload tiering, rightsizing, and chargeback readiness.
 </li>
 <li>
 Translate cloud cost outcomes into commercial terms understood by finance and business stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Technical Leadership
 
 
 <ul>
 <li>
 Work closely with the Data Architect, Data Engineer, Data Analyst, Data Scientist, and AI Engineer to set and uphold technical standards.
 </li>
 <li>
 Provide hands-on technical guidance and code review across the team.
 </li>
 <li>
 Translate business requirements into technical designs with clear delivery outcomes.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 Minimum of 7 years in data engineering or data platform work, with strong hands-on delivery experience.
 </li>
 <li>
 At least 3 years hands-on with Databricks, Apache Spark, and Delta Lake at enterprise scale. Snowflake or BigQuery experience is acceptable where the CV shows a real Databricks migration.
 </li>
 <li>
 Contributed to the build or rebuild of an enterprise data platform serving multiple business domains.
 </li>
 <li>
 Deep hands-on experience with the Azure data stack: Databricks, ADLS, Azure Data Factory, Synapse, Azure SQL, Fabric.
 </li>
 <li>
 Direct experience integrating heavy ERP sources: Oracle Fusion, Hyperion, CMiC, or equivalent estates.
 </li>
 <li>
 Governance shipped to production using Unity Catalog or Microsoft Purview, with PDPL or GDPR controls operational, not theoretical.
 </li>
 <li>
 Practical FinOps outcomes on cloud spend.
 </li>
 <li>
 Strong on CI/CD, Git, Azure DevOps, and infrastructure-as-code (Terraform or Bicep).
 </li>
 <li>
 Excellent written and verbal communication skills across technical and business audiences.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Direct experience of a Synapse Analytics to Databricks migration.
 </li>
 <li>
 Exposure to MLOps and LLMOps stacks: MLflow, feature store, vector stores, RAG, agent frameworks.
 </li>
 <li>
 Familiarity with Power BI semantic models and enterprise BI governance.
 </li>
 <li>
 Streaming and event-driven experience: Kafka, Event Hubs, Structured Streaming.
 </li>
 <li>
 Multi-entity, multi-country group exposure with mixed data residency considerations.
 </li>
 <li>
 Industry experience in construction, engineering services, manufacturing, energy, or logistics.
 </li>
 </ul>
 
 
 
 
 
 Certifications
 
 
 
 
 
 Mandatory:
 
 
 
 <ul>
 <li>
 
 Databricks Certified Data Engineer Professional
 
 (Candidates holding the Associate level will be considered on the condition that Professional is achieved within 6 months of joining.)
 </li>
 </ul>
 
 
 Preferred (one or more):
 
 
 <ul>
 <li>
 
 Databricks Certified Machine Learning Professional
 
 </li>
 <li>
 
 Databricks Certified Generative AI Engineer Associate
 
 </li>
 <li>
 
 Microsoft Certified: Azure Data Engineer Associate
 
 (DP-203 / DP-700)
 </li>
 <li>
 
 Microsoft Certified: Fabric Analytics Engineer Associate
 
 (DP-600)
 </li>
 <li>
 
 Microsoft Certified: Azure Solutions Architect Expert
 
 </li>
 <li>
 
 Certified Data Management Professional (CDMP)
 
 &mdash; DAMA
 </li>
 </ul>
 
 
 Education
 
 
 
 M.Tech / B.E. / B.Tech (Computer Science, Information Systems, IT) / MCA / MCS.
 
</div>

Data Platform Lead

Easygenerator

<div>
 
 Join Easygenerator and build the data platform powering the future of learning
 
 
 
 Step into an exciting role with an innovative e-learning software company in the EdTech space as a
 
 Data Engineer
 
 .
 
 
 Easygenerator is a fast-growing scale-up revolutionizing e-learning with our award-winning authoring tool. Join us to build scalable data solutions that enable smarter decisions across Product, Marketing, Revenue, and Business Intelligence.
 
 
 What's in it for you?
 
 
 <ul>
 <li>
 Grow Your Career: Take ownership of our modern data platform and work on high-impact projects spanning analytics, AI, and business intelligence.
 </li>
 <li>
 International Environment: Join a dynamic, international team (40+ nationalities) in a fast-growing scale-up where your work directly influences business outcomes.
 </li>
 <li>
 AI-First Company: We embrace AI in both our product and internal operations. You'll gain hands-on experience with AI-powered analytics and emerging data technologies.
 </li>
 <li>
 Learning &amp; Development: Access continuous coaching, learning opportunities, and the freedom to explore new technologies and best practices.
 </li>
 <li>
 Hybrid Working Policy: 3 day on-site / 2-day Work from Home (WFH) split.
 
 
 </li>
 </ul>
 What you will be doing
 
 
 <ul>
 <li>
 Build and maintain scalable data pipelines and infrastructure using Snowflake, AWS Glue, and modern ETL/ELT frameworks.
 </li>
 <li>
 Integrate data from platforms such as Salesforce, Mixpanel, Segment, Customer.io, Intercom, Google Analytics, and LinkedIn Ads.
 </li>
 <li>
 Develop reliable data models, warehouses, and data lakes to support reporting and analytics.
 </li>
 <li>
 Implement data quality, monitoring, governance, and security best practices.
 </li>
 <li>
 Build AI-powered self-service analytics capabilities for business users.
 </li>
 <li>
 Partner with Product, Marketing, Revenue Operations, and BI teams to deliver impactful data solutions.
 </li>
 <li>
 Optimize platform performance, reliability, and cost efficiency.
 
 
 </li>
 </ul>
 What you will bring
 
 
 <ul>
 <li>
 5+ years of Data Engineering experience.
 </li>
 <li>
 Strong expertise in Snowflake, including architecture, performance optimization, governance, and security.
 </li>
 <li>
 Experience with AWS Glue (PySpark), ETL/ELT pipelines, and workflow orchestration.
 </li>
 <li>
 Advanced SQL and Python skills.
 </li>
 <li>
 Experience with PostgreSQL, MongoDB, Amazon S3, and modern cloud data architectures.
 </li>
 <li>
 Strong understanding of data modelling, warehousing, and analytics engineering practices.
 </li>
 <li>
 Experience integrating SaaS platforms and customer, product, marketing, or revenue data.
 </li>
 <li>
 Knowledge of data governance, privacy, and compliance frameworks such as GDPR.
 </li>
 <li>
 Strong problem-solving skills, ownership mindset, and attention to detail.
 
 
 </li>
 </ul>
 Nice to have
 
 
 <ul>
 <li>
 Experience in a B2B SaaS environment.
 </li>
 <li>
 Power BI experience, including data modeling and DAX.
 </li>
 <li>
 Experience with Snowflake Cortex AI and AI-powered analytics solutions.
 </li>
 <li>
 Knowledge of marketing attribution and revenue analytics.
 </li>
 <li>
 Experience with Streamlit, Mixpanel, or similar analytics tools.
 
 
 </li>
 </ul>
 Ready to Join Us?
 
 
 If you're passionate about building modern data platforms and helping teams make smarter decisions with data, we'd love to hear from you. Apply today!
 
 
</div>

Data Engineer

GlobalDrum

<div>
 
 
 Role: Backend Engineer (AI-First)
 
 
 
 
 
 
 
 
 Location:
 
 Dubai / Hybri
 
 
 
 dDepartment:
 
 Technology &amp; Operation
 
 
 
 sReports To
 
 : CI
 
 
 
 OPosition:
 
 Full-Tim
 
 
 
 
 
 
 e
 
 About u
 
 
 
 s:GlobalDrum is empowering the media sector to own, understand, and monetise their most valuable social audiences, using live audience behavioral data for brands to operate diversified business models on demand for themselve
 
 
 
 
 
 s.
 
 We are evolving our unique next-generation B2B2C Platform as a Service (PaaS) that operates on a globally distributed cloud infrastructure incorporating a scalable, event-driven architecture using the latest AI and data techniques to evolve an entire sect
 
 
 
 
 
 or.
 
 Located in London, Dubai, New York and Dubai, the Company is at the centre of reshaping how global brands will evolve in a sector valued at $276Bn in 2025 representing 30% of all digital ad spend
 
 
 ing.If this seems too ambitious for you, then don't ap
 
 
 
 
 
 
 ply.
 
 Job Descrip
 
 
 
 tion:Are you an AI pioneer who still loves to get your hands dirty in the code
 
 
 
 
 
 base?
 
 We are looking for a visio
 
 nary, hands-on AI/Backend Eng
 
 ineer to be a core builder of our multi-tenant platform. Working within a fast-paced development team in Dubai, you will architect and deploy the complex backend systems that drive monetisation such as content ingestion, ad-serving, and subscriptions. You will heavily leverage AI development tools to write, test, and ship AWS or cloud-agnostic code at unprecedented s
 
 
 
 
 
 peeds.
 
 If you thrive in a fast-paced environment and have a proven track record of building massive, data-intensive global systems, we want you as part of our engineerin
 
 
 
 
 
 
 g team.
 
 Key Responsib
 
 
 <ul>
 <li>
 ilities:Develop, test, and maintain backend services and public APIs for our multi-tenant SaaS p
 </li>
 <li>
 latform.Integrate third-party systems, including ad networks, subscription billing, and MCP so
 </li>
 <li>
 lutions.Write clean, efficient code while maximizing output through the use of agentic A
 </li>
 <li>
 I tools.Actively participate in daily stand-ups, sprint planning, and other Scrum cer
 </li>
 </ul>
 
 
 
 
 
 emonies.
 
 Required Skills and Qualif
 
 
 <ul>
 <li>
 ications:Proven experience in large-scale AI-assisted development and utilizing agentic w
 </li>
 <li>
 orkflows.Solid understanding of Solution Architecture, AWS, and cloud-agnostic infras
 </li>
 <li>
 tructure.Demonstrable experience working in fast-moving startup envi
 </li>
 <li>
 ronments.Practical experience operating within a strict Scrum/Agile f
 </li>
 </ul>
 
 
 
 
 
 ramework.
 
 Preferred Experience/Quali
 
 
 <ul>
 <li>
 fications:Hands-on experience with SaaS/PaaS platforms and multi-tenant arch
 </li>
 <li>
 itectures.Familiarity with MarTech, AdTech, payment systems, and MCP
 </li>
 </ul>
 
 
 
 
 
 solutions.
 
 Bonus Points If
 
 
 
 You Have...While not strictly required, exposure to the following will make you a standout
 
 <ul>
 <li>
 candidate:Deep understand
 
 ing of the Media
 
 and/or News technology
 </li>
 <li>
 ecosystems.Exp
 
 erienc
 
 e in AdTech (advertising networks, programmatic bidding, a
 </li>
 <li>
 d
 
 serving).A Startup/Scale-up
 
 background, bringing a strategic, client-centric, and solution-oriented mindset to technical probl
 </li>
 </ul>
 
 
 
 
 
 em-solving.
 
 
 
 <ul>
 <li>
 Why Join Us?The chance to build a ground-breaking AI platform
 </li>
 <li>
 from day oneCompetitive equity options packag
 </li>
 <li>
 e and salaryFlexible working
 </li>
 </ul>
 
 
 
 environment
</div>

Backend Engineer (AI-First)

Involved Solutions

<div>
 
 We have partnered with a fast-growing ecommerce business in Dubai to hire a DevOps Engineer. This is a business where platform performance is not a nice to have, it is everything. Uptime, deployment speed and infrastructure reliability directly affect revenue, and the engineering team knows it. You will be joining at a point where the platform is scaling fast and the decisions you make will have a real and visible impact on how the business operates.
 
 
 
 
 This role suits an engineer who takes pride in building infrastructure that holds up under pressure and a deployment pipeline that lets the rest of the engineering team move fast with confidence.
 
 
 
 
 About the role:
 
 <ul>
 <li>
 Own and evolve the cloud infrastructure, ensuring environments are scalable, resilient and optimised for a high-traffic ecommerce platform
 </li>
 <li>
 Build and maintain CI/CD pipelines that enable fast, reliable and repeatable software delivery across multiple teams
 </li>
 <li>
 Lead containerisation and orchestration across development, staging and production environments using Kubernetes and Docker
 </li>
 <li>
 Implement and maintain infrastructure-as-code using tools such as Terraform or Ansible, reducing manual processes and increasing consistency
 </li>
 <li>
 Define and own observability standards including logging, monitoring, alerting and incident response
 </li>
 <li>
 Work closely with software engineering teams to embed DevOps culture and shared ownership across the delivery lifecycle
 </li>
 <li>
 Contribute to platform architecture decisions with a focus on reliability, cost efficiency and scale
 </li>
 </ul>
 
 
 
 About you:
 
 <ul>
 <li>
 3 to 5 years of experience in DevOps, platform or infrastructure engineering roles
 </li>
 <li>
 Hands-on experience with at least one major cloud provider, AWS, GCP or Azure, with a solid understanding of cloud-native services
 </li>
 <li>
 Production-level experience with Kubernetes and container orchestration
 </li>
 <li>
 Proven track record building and managing CI/CD pipelines using tools such as GitHub Actions, GitLab CI or Jenkins
 </li>
 <li>
 Proficiency with infrastructure-as-code tooling, particularly Terraform
 </li>
 <li>
 Solid understanding of networking, security fundamentals and cloud cost management
 </li>
 <li>
 Ecommerce or high-traffic consumer platform experience is a strong advantage
 </li>
 </ul>
</div>

Senior DevOps 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

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

Delivery Hero

<div>Company Description 
Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat&rsquo;s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.
We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.
Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner. 
Job Description 
As the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users. 
 
As a Senior Analytics Engineer, you will be responsible for transforming raw data into well-structured, reliable, and accessible data models that enable analysts, data scientists, and business stakeholders to make informed decisions. You will work closely with data engineers to build scalable data pipelines and collaborate with analysts to ensure data is actionable and insightful.<ul><li>
Design, build, and maintain clean, efficient, and scalable data models in SQL and dbt. Optimize query performance and data processing efficiency.</li><li>
Ensure data is structured to support self-service analytics and business intelligence.</li><li>
Work closely with data engineers to define data requirements and enhance ETL pipelines.</li><li>
Partner with product analysts, data scientists, and business teams to ensure data meets analytical and reporting needs.</li><li>
Implement and enforce data quality best practices to ensure accuracy and consistency.</li><li>
Develop and maintain data transformation workflows using dbt, SQL, and cloud-based data platforms. Automate data validation and reporting processes.</li><li>
Monitor data integrity and troubleshoot data issues proactively. Advocate for best practices in documentation, testing, and version control.</li></ul> 
Qualifications<ul><li> 
Bachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.</li><li>
Strong proficiency in Python, SQL and experience with dbt for data modeling.</li><li>
Experience working with cloud-based data warehouses (e.g., Snowflake, BigQuery, GCP, Redshift).</li><li>
Familiarity with version control (Git) and CI/CD practices for data workflows.</li><li>
Understanding of data engineering principles, including ETL/ELT processes.</li></ul></div>

Senior Analytics Engineer

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