platform engineer

Tata Consultancy Services

<div>
 
 
 Job Title
 
 &ndash; AI Platform 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:
 
 
 
 
 AI Platform Operations
 
 
 
 Provide day-to-day monitoring and operational support of Gernas, its dependent AI applications, deployed AI agents, agent runtime environments, AI gateways, and supporting Azure and AWS cloud services. Ensure continuous availability and consistent service performance across production environments, proactively identifying degradation signals before they become user-visible incidents. Maintain operational dashboards covering platform health, agent execution, LLM consumption, gateway throughput, and integration endpoints, and ensure that ownership of every production component is unambiguous and documented.
 
 
 
 Incident and Problem Management
 
 
 
 Lead L2 and L3 incident response across the Gernas platform and its surrounding AI products. Conduct structured root-cause analysis, drive service restoration within agreed P1&ndash;P4 service-level commitments, and coordinate major incidents involving multiple engineering, cloud, security, and vendor stakeholders. Maintain problem records for recurring or systemic issues, ensure that post-incident reviews are completed with clear corrective and preventive actions, and own the closure of those actions through to engineering remediation. Act as the bridge between the L1 AI Operations Centre and L3 engineering teams during complex incidents.
 
 
 
 AI Agent and Workflow Support
 
 
 
 Troubleshoot the behaviour of single-agent and multi-agent workflows, including agent orchestration, tool invocation, skill execution, prompt construction, memory and context handling, planning loops, and inter-agent coordination. Diagnose failures across Microsoft Agent Framework and LangGraph execution, including state-graph traversal, conditional routing, tool-call mismatches, retries, and human-in-the-loop checkpoints. Investigate integrations with enterprise systems, MCP-exposed tools, and downstream APIs, and work with engineering teams to harden agent designs where production data reveals weaknesses.
 
 
 
 LLM and Model Service Support
 
 
 
 Support the operational stability of the model-serving layer across Azure OpenAI PTU deployments, AWS Bedrock, and Core42 Compass. Monitor and troubleshoot PTU capacity utilisation, token consumption patterns, quota and throttling behaviour, latency profiles, content filtering outcomes, and model endpoint availability. Coordinate with the AI Hub team on routing decisions between frontier and in-region models, assess cost and capacity headroom, and manage capacity escalations and vendor tickets where service degradation originates upstream.
 
 
 
 AKS and Runtime Support
 
 
 
 Provide hands-on operational support of the Azure Kubernetes Service estate hosting Gernas agent runtimes and supporting services. Troubleshoot pod, deployment, service, ingress, namespace, secret, and configuration issues; investigate autoscaling behaviour and resource utilisation anomalies; and analyse container logs, network connectivity, and runtime failures. Work closely with the Cloud Platform team on cluster-level concerns, image security, node health, and platform upgrades, ensuring AKS-hosted workloads remain stable through patching and lifecycle events.
 
 
 
 API, AI Gateway and MCP Support
 
 
 
 Operate and troubleshoot the Azure API Management layer that serves as both the enterprise API gateway and the MCP Gateway for Gernas. Diagnose issues with API policies, authentication, authorisation, routing, rate limiting, quotas, caching, and backend connectivity. Provide deep support for MCP servers, MCP tools, and the MCP Gateway pattern &mdash; including tool discovery, schema validation, protocol-level failures, and the coordination between MCP clients hosted in agents and the underlying tool endpoints. Ensure that the gateway remains a secure, observable, and policy-compliant control plane for all AI traffic.
 
 
 
 Observability and Performance Management
 
 
 
 Use Comet Opik as the primary observability surface for agent and LLM execution, working with traces, prompts, agent execution paths, latency breakdowns, token usage, errors, and model quality indicators. Build and maintain operational dashboards, alert rules, and correlation views that combine Opik telemetry with Azure Monitor, Application Insights, Log Analytics, and CloudWatch data. Lead performance optimisation initiatives where trace evidence shows hotspots in prompts, tools, retrieval steps, or model selection, and ensure that observability coverage keeps pace with platform evolution.
 
 
 
 Voice AI Support
 
 
 
 Support the production operation of ElevenLabs-based voice AI capabilities, including speech generation, voice-agent connectivity, real-time audio session handling, and API consumption patterns. Investigate latency, audio quality, dropped sessions, and integration failures across the voice channel and its dependent platforms, and coordinate with ElevenLabs and integration partners on upstream issues.
 
 
 
 Release and Change Management
 
 
 
 Validate releases prior to and immediately following deployment, exercising production verification scripts, smoke tests, and rollback procedures. Maintain release readiness through clear configuration management, environment parity checks, and pre-deployment risk reviews. Operate within FAB's change-management framework, ensuring that all production changes including patches, upgrades, configuration adjustments, and model or prompt rotations pass through the appropriate change controls and post-implementation review.
 
 
 
 Security, Risk and Compliance
 
 
 
 Uphold the security and compliance posture of Gernas and dependent AI products. Manage identity and access controls, secrets, certificates, and managed identities across the platform; coordinate vulnerability remediation and patching cycles; and maintain audit evidence for internal audit, supervisory reviews, and external assurance. Operate responsible-AI controls including content filtering, PII and PCI detection, data egress controls, and model-access governance and ensure that secure integration patterns are followed across every API, MCP tool, and external dependency.
 
 
 
 Service Improvement and Automation
 
 
 
 Drive continuous reduction of manual support effort through automation of routine operational tasks, self-healing patterns, monitoring enhancements, and proactive remediation. Maintain a current and high-quality library of support playbooks, runbooks, knowledge articles, and standard operating procedures. Identify and lead service-improvement initiatives that lift platform reliability metrics, reduce incident volume, and shorten mean time to resolution.
 
 
 
 Stakeholder and Vendor Coordination
 
 
 
 Operate as a credible technical counterpart to business units, engineering teams, the Cloud Platform team, Cybersecurity, Architecture, AI Governance, and Service Management. Lead vendor engagement with Microsoft, AWS, Core42, ElevenLabs, and other technology partners on incidents, capacity reviews, roadmap items, and product issues, ensuring that vendor accountability is exercised and that escalations are progressed effectively.
 
 
 
 On-Call and Operational Readiness
 
 
 
 Participate in a 24&times;7 support model, including a structured on-call rotation, major incident leadership, disaster-recovery exercises, business-continuity testing, and production-readiness assessments for new agents, models, and integrations entering the platform. Treat operational readiness as a release gate rather than an afterthought, and ensure that nothing reaches production without explicit operational sign-off.
 
 
 
 
 
 
 TECHNICAL SKILLS: minimum 5-7 yrs of working experience mandatory
 
 
 
 
 Cloud AI Services
 
 
 
 
 
 
 
 Agentic AI Frameworks
 
 
 
 
 LLM Operations
 
 
 
 
 Kubernetes and Containers
 
 
 
 
 API and MCP Gateway
 
 
 
 
 Observability
 
 
 
 
 DevOps and Automation
 
 
 
 
 Voice AI
 
 
 
 
 Security and Governance
 
 
 
 
 Service Management
 
 
 
 
 
 
 
 KNOWLEDGE, SKILLS, &amp; EXPERIENCE
 
 
 
 
 Education
 
 
 
 Bachelor's degree in Computer Science, Artificial Intelligence, Information Technology, Engineering, or a closely related discipline. A relevant master's degree in AI, Machine Learning, or Cloud Computing will be considered an advantage.
 
 
 
 Professional Experience
 
 
 
 Approximately 5&ndash;7 years of overall IT experience, with significant time spent in cloud application support, platform engineering, DevOps, Site Reliability Engineering, production operations, or senior technical support roles. Of this, a minimum of 2&ndash;3 years of relevant experience supporting AI, machine learning, Generative AI, conversational AI, cloud-native platforms, or other data-intensive enterprise systems is required.
 
 
 
 Banking and Regulated Environment
 
 
 
 
 
 
 
 Technical Troubleshooting
 
 
 
 
 
 
 
 Operational Skills
 
 
 
 
 
 
 
 Communication and Leadership
 
 
 
 
 
 
 
 
 
 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 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

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

GSSTech Group

<div>We are looking for an experienced Senior DevOps Engineer with strong expertise in OpenShift Platform Administration, Kubernetes, and CI/CD engineering to support large-scale Business Platforms &amp; Payments initiatives.
The ideal candidate should have hands-on experience managing enterprise container platforms, building and maintaining CI/CD pipelines, automating deployment processes, and supporting mission-critical payment applications. The role requires working in a fast-paced environment where frequent releases and high-velocity payment changes are delivered while ensuring platform stability, security, and high availability. 
Requirements 
 
Key Responsibilities<ul><li>
Design, build, and maintain enterprise CI/CD pipelines for mission-critical applications.</li><li>
Administer and manage OpenShift container platform environments.</li><li>
Deploy, configure, and manage Kubernetes clusters and containerized workloads.</li><li>
Develop, maintain, and optimize Jenkins pipelines using Groovy scripting and Shared Libraries.</li><li>
Implement GitOps deployment strategies using Argo CD.</li><li>
Create, maintain, and manage Helm Charts for Kubernetes application deployments.</li><li>
Manage source code repositories and branching strategies using Git.</li><li>
Support application deployment, release management, and environment provisioning.</li><li>
Monitor platform health, troubleshoot deployment issues, and optimize application performance.</li><li>
Work closely with Development, QA, Infrastructure, Security, and Operations teams to streamline software delivery.</li><li>
Support high-frequency production releases and mission-critical payment platform deployments.</li><li>
Ensure platform security, scalability, availability, and compliance with enterprise standards.</li><li>
Participate in release planning, production support, incident management, and root cause analysis.</li><li>
Automate operational tasks and continuously improve DevOps processes and engineering practices.</li><li>
Document deployment procedures, platform architecture, and operational standards.</li></ul>
Required Technical Skills<ul><li>
Strong hands-on experience with Kubernetes administration.</li><li>
Strong experience administering Red Hat OpenShift Platform (OpenShift Container Platform).</li><li>
Expertise in Jenkins CI/CD pipeline development and administration.</li><li>
Strong hands-on experience writing Groovy-based Jenkins Pipelines.</li><li>
Experience developing and maintaining Jenkins Shared Libraries.</li><li>
Strong experience with Argo CD (GitOps deployment).</li><li>
Hands-on experience creating and managing Helm Charts.</li><li>
Strong proficiency with Git version control, branching strategies, and repository management.</li><li>
Experience deploying and managing containerized applications in enterprise Kubernetes environments.</li><li>
Strong understanding of CI/CD best practices and DevOps automation.</li><li>
Experience troubleshooting deployment failures, pipeline issues, and platform incidents.</li><li>
Strong Linux administration knowledge.</li><li>
Experience working with REST APIs and deployment automation.</li></ul>
Nice to Have<ul><li>
Experience with Istio Service Mesh.</li><li>
Experience with 3scale API Management.</li><li>
Exposure to payment platforms or financial services environments.</li><li>
Experience supporting high-volume transaction systems.</li><li>
Knowledge of enterprise monitoring and logging tools.</li><li>
Experience with Infrastructure as Code (Terraform, Ansible, or similar).</li><li>
Exposure to cloud platforms (AWS, Azure, or GCP).</li></ul>
Required Competencies<ul><li>
Strong analytical and troubleshooting skills.</li><li>
Excellent communication and stakeholder management.</li><li>
Ability to work in fast-paced, high-pressure production environments.</li><li>
Strong ownership mindset with excellent attention to detail.</li><li>
Ability to manage multiple priorities and critical production releases.</li><li>
Collaborative team player with strong problem-solving capability.</li><li>
Ability to work independently while supporting cross-functional engineering teams.</li></ul>
Preferred Domain Experience<ul><li>
Banking</li><li>
Payments</li><li>
Financial Services</li><li>
Enterprise Digital Platforms</li><li>
Mission-Critical Production Systems</li></ul>
Education
Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related discipline (or equivalent industry experience).</div>

Senior DevOps Engineer (OpenShift)

Global Software Solutions Group

<div>
 We are looking for an experienced Senior DevOps Engineer with strong expertise in OpenShift Platform Administration, Kubernetes, and CI/CD engineering to support large-scale Business Platforms &amp; Payments initiatives.
 
 
 The ideal candidate should have hands-on experience managing enterprise container platforms, building and maintaining CI/CD pipelines, automating deployment processes, and supporting mission-critical payment applications. The role requires working in a fast-paced environment where frequent releases and high-velocity payment changes are delivered while ensuring platform stability, security, and high availability.
 
 
 
 Requirements
 
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and maintain enterprise CI/CD pipelines for mission-critical applications
 </li>
 <li>
 Administer and manage OpenShift container platform environments
 </li>
 <li>
 Deploy, configure, and manage Kubernetes clusters and containerized workloads
 </li>
 <li>
 Develop, maintain, and optimize Jenkins pipelines using Groovy scripting and Shared Libraries
 </li>
 <li>
 Implement GitOps deployment strategies using Argo CD
 </li>
 <li>
 Create, maintain, and manage Helm Charts for Kubernetes application deployments
 </li>
 <li>
 Manage source code repositories and branching strategies using Git
 </li>
 <li>
 Support application deployment, release management, and environment provisioning
 </li>
 <li>
 Monitor platform health, troubleshoot deployment issues, and optimize application performance
 </li>
 <li>
 Work closely with Development, QA, Infrastructure, Security, and Operations teams to streamline software delivery
 </li>
 <li>
 Support high-frequency production releases and mission-critical payment platform deployments
 </li>
 <li>
 Ensure platform security, scalability, availability, and compliance with enterprise standards
 </li>
 <li>
 Participate in release planning, production support, incident management, and root cause analysis
 </li>
 <li>
 Automate operational tasks and continuously improve DevOps processes and engineering practices
 </li>
 <li>
 Document deployment procedures, platform architecture, and operational standards
 
 
 </li>
 </ul>
 
 Required Technical Skills
 
 
 
 <ul>
 <li>
 Strong hands-on experience with Kubernetes administration
 </li>
 <li>
 Strong experience administering Red Hat OpenShift Platform (OpenShift Container Platform)
 </li>
 <li>
 Expertise in Jenkins CI/CD pipeline development and administration
 </li>
 <li>
 Strong hands-on experience writing Groovy-based Jenkins Pipelines
 </li>
 <li>
 Experience developing and maintaining Jenkins Shared Libraries
 </li>
 <li>
 Strong experience with Argo CD (GitOps deployment)
 </li>
 <li>
 Hands-on experience creating and managing Helm Charts
 </li>
 <li>
 Strong proficiency with Git version control, branching strategies, and repository management
 </li>
 <li>
 Experience deploying and managing containerized applications in enterprise Kubernetes environments
 </li>
 <li>
 Strong understanding of CI/CD best practices and DevOps automation
 </li>
 <li>
 Experience troubleshooting deployment failures, pipeline issues, and platform incidents
 </li>
 <li>
 Strong Linux administration knowledge
 </li>
 <li>
 Experience working with REST APIs and deployment automation
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience with Istio Service Mesh
 </li>
 <li>
 Experience with 3scale API Management
 </li>
 <li>
 Exposure to payment platforms or financial services environments
 </li>
 <li>
 Experience supporting high-volume transaction systems
 </li>
 <li>
 Knowledge of enterprise monitoring and logging tools
 </li>
 <li>
 Experience with Infrastructure as Code (Terraform, Ansible, or similar)
 </li>
 <li>
 Exposure to cloud platforms (AWS, Azure, or GCP)
 
 
 </li>
 </ul>
 
 Required Competencies
 
 
 
 <ul>
 <li>
 Strong analytical and troubleshooting skills
 </li>
 <li>
 Excellent communication and stakeholder management
 </li>
 <li>
 Ability to work in fast-paced, high-pressure production environments
 </li>
 <li>
 Strong ownership mindset with excellent attention to detail
 </li>
 <li>
 Ability to manage multiple priorities and critical production releases
 </li>
 <li>
 Collaborative team player with strong problem-solving capability
 </li>
 <li>
 Ability to work independently while supporting cross-functional engineering teams
 
 
 </li>
 </ul>
 
 Preferred Domain Experience
 
 
 
 <ul>
 <li>
 Banking
 </li>
 <li>
 Payments
 </li>
 <li>
 Financial Services
 </li>
 <li>
 Enterprise Digital Platforms
 </li>
 <li>
 Mission-Critical Production Systems
 
 
 </li>
 </ul>
 
 Education
 
 
 
 Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related discipline (or equivalent industry experience).
</div>

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

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>

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