devops engineer

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cloud and devops engineer Jobs in Abu Dhabi

cloud and devops engineer

devops engineer (6 months contract) Jobs in Abu Dhabi

devops engineer (6 months contract)

devops solutions architect

UNISON Group

<p></p><div><ul><li>We&rsquo;re seeking a hands-on experience in Databricks with deep technical expertise in building and optimizing Lakehouse-based data and AI solutions.
</li><li>In this role, you&rsquo;ll design, develop, and operationalize Delta Lakehouse architectures using Databricks, driving real-world outcomes for enterprise customers. You&rsquo;ll take ownership of implementation tasks, lead technical delivery, and mentor engineering teams in best practices across data engineering, governance, and AI.</li></ul><p>
</p><p><b>Key Responsibilities</b></p><ul><li>
Design and implement scalable data pipelines using Delta Live Tables (DLT), Spark SQL, Python, or Scala.</li><li>
Optimize ETL, streaming, and ML workloads for performance, cost efficiency, and reliability.</li><li>
Administer and configure Databricks Workspaces, Unity Catalog, and cluster policies for secure, governed environments.</li><li>
Automate infrastructure and deployments using Terraform, Git, and CI/CD pipelines.</li><li>
Implement observability, cost optimization, and monitoring frameworks using tools like Splunk, Prometheus, or CloudWatch.</li><li>
Collaborate with customers to build AI and LLM solutions leveraging MLflow, DBRX, and Mosaic AI.</li></ul><p></p><p><br>
</p><br>
<br>
<p></p><b>Requirements</b><p><b><br>
Required Skills &amp; Experience</b></p><p>
</p><ul><li>Strong 10+ hands-on experience with Databricks, including workspace setup, notebooks, clusters, and job orchestration.</li><li>
Expertise in Delta Lake, DLT, Unity Catalog, and SQL Warehouses.</li><li>
Strong 8+ Years of experience with Spark</li><li>
Proficiency in Python or Scala for data engineering and ML workflows.</li><li>
Strong understanding of AWS, Azure, or GCP cloud ecosystems.</li><li>
Experience with Terraform automation, DevOps, and MLOps practices.</li><li>
Familiarity with monitoring and governance frameworks for large-scale data platforms.</li></ul></div><p></p>

Databricks Solution Architect

bankfab

<div><div>Job Description</div>
<div>
 <p><b>JOB SUMMARY / INTRODUCTION
</b></p><ul><li>To lead the engineering, architecture, and run-state ownership of the bank's enterprise AI &amp; Agentic Platform, ensuring it operates as a reliable, secure, observable, and bank-grade production platform supporting agents and AI workloads across the Group.
</li><li>The role is the senior technical authority for platform engineering and architecture across the agentic runtime, model gateway, integration fabric, identity layer, and infrastructure backbone of the platform.
</li><li>It operates in a two-in-a-box model with the existing Platform Product Owner to provide concurrent technical ownership and organizational resilience for the platform, with shared accountability for platform availability, performance, cost, security posture, and architectural evolution.
</li>The role is deeply technical in nature, requiring hands-on engineering depth across distributed systems, agentic protocols, LLM infrastructure, identity and access management, and cloud-native platform engineering.<br>
<li>
 </li></ul><p></p><p><b>KEY RESPONSIBILITIES
 </b></p><p><b>Key Accountabilities &mdash; Platform Architecture<br>
</b><br>
</p><ul><li>Own the end-to-end technical architecture of the AI &amp; Agentic Platform's five-layer stack: Action Gateway, Agent Kernel, Control Plane, Knowledge Foundation, and the Users and Channels layer.
</li><li>Architect and evolve the agentic runtime to natively support the emerging multi-protocol stack: Model Context Protocol (MCP) for agent-to-tool access, Agent-to-Agent (A2A) for inter-agent coordination and task delegation, Agent Communication Protocol (ACP) and equivalent emerging standards, ensuring the platform is interoperable with hyperscaler agent fabrics (Azure AI Foundry agents, AWS Bedrock Agents, Google ADK).
</li><li>Design the platform's agent kernel, including agent lifecycle management, planning and reasoning loops, memory architecture (short-term, long-term, episodic), state management, session affinity, scratchpad persistence, and execution chains.
</li><li>Architect the platform's knowledge foundation, including vector store selection and topology, hybrid retrieval (BM25, dense, graph), embeddings strategy, knowledge graph integration (FIBO, OWL, SHACL, SPARQL), context engineering, and grounding patterns.
</li><li><p>Design the platform's control plane, including policy-gated execution, Know Your Agent (KYA) enforcement at runtime, agent registries, tool registries, capability discovery, evaluation pipelines, and tracing and lineage at agent and tool granularity.
</p><p><b>Key Accountabilities &mdash; Integrations &amp; Model Layer
</b></p></li><li>Architect and engineer the platform's LLM gateway and model abstraction layer, providing a unified interface across foundation model providers (Azure AI Foundry, AWS Bedrock, OpenAI, Anthropic, Google Vertex AI, Cohere) with intelligent routing, fallback, retries, prompt and response caching, semantic caching, rate limiting, token accounting, cost attribution, and tenant isolation.
</li><li>Design model serving patterns for managed APIs, dedicated capacity (PTUs / provisioned throughput), and self-hosted open-weight models on GPU infrastructure (vLLM, TGI, Triton, or equivalent), with appropriate trade-offs across cost, latency, sovereignty, and compliance.
</li><li>Lead the integration architecture between the AI Platform and the bank's core estate, including core banking, payments, treasury, credit and risk systems, the enterprise data platform (Azure, Cloudera, Databricks), enterprise APIs, ESB, event streaming (Kafka, Event Hubs), and the data product layer.
<br>
Design the action gateway as the bank's enforcement boundary for agentic action, including API mediation, contract enforcement, circuit breakers, idempotency guarantees, transactional safety, and audit-grade action logging.
</li><li><p>Engineer the platform's tool layer and MCP server estate, including tool packaging, versioning, capability advertisement, schema enforcement, and runtime tool discovery across Wholesale, Retail, and Group functions.
</p><p><b>Key Accountabilities &mdash; Identity, Security &amp; Governance
</b></p></li><li>Architect and own the agent identity and workload identity model for the platform, including non-human identity (NHI) management, agent identity lifecycle, blended user-plus-agent identity for delegated actions, and the identity propagation chain across multi-agent flows.
<br>
Design the platform's authentication and authorization architecture, including OAuth 2.1 and OIDC flows for agent-to-tool and agent-to-API interactions, just-in-time credential issuance, short-lived token exchange, mTLS for agent-to-agent communication, and integration with the bank's enterprise IAM (Microsoft Entra ID, PAM, secrets management).
</li><li>Implement zero-trust principles across the agentic stack, including least-privilege scoping per agent and per task, real-time policy evaluation, behavioral posture checks, and continuous authorization rather than static service-account-style access.
</li><li>Engineer the platform's runtime governance controls, including KYA enforcement, prompt and output guardrails (PII, PHI, MNPI, prompt injection defense), sensitive action approval flows, and human-in-the-loop escalation patterns.
</li><li>Harden the platform to meet CBUAE, internal model risk, and Group governance requirements, including auditability, lineage, data residency, model risk controls, third-party model governance, and OWASP LLM Top 10 alignment.
</li><li>Key Accountabilities &mdash; Infrastructure &amp; Run-State
</li><li>Lead the platform's cloud and infrastructure architecture across Azure (primary) and AWS, including infrastructure as code (Terraform), networking (private endpoints, peering, egress control), Kubernetes (AKS) and container orchestration, secrets management, and CI/CD pipelines.
</li><li>Own platform Site Reliability Engineering (SRE), including SLO design, error budget management, observability (OpenTelemetry, traces, metrics, logs at agent and tool granularity), incident response, post-mortems, capacity planning, and cost governance for a growing fleet of agents and AI workloads in production.
<br>
Operate in genuine two-in-a-box with the existing Platform Product Owner, including shared on-call, shared roadmap ownership, and shared accountability for major architectural decisions, regulator conversations, and critical incidents.
</li><li>Drive engineering excellence across the platform team, including testing discipline (unit, integration, evaluation, red-teaming), documentation, infrastructure as code maturity, operational readiness reviews, and technical mentorship of platform engineers.
</li><li>Represent the platform in senior technical forums with Enterprise Architecture, Cyber, Model Risk, Internal Audit, and the Group CTTO's office on architecture and engineering matters.
</li><li><p>Engage with hyperscale, model provider, and framework vendor technical teams on platform-level integration, performance, sovereignty, and cost optimization.
</p><p><b>REQUIREMENTS / QUALIFICATIONS
</b></p><p><b>Technical Expertise
</b></p></li><li>Deep, current expertise in agentic AI architecture and the modern multi-protocol stack: Model Context Protocol (MCP), Agent-to-Agent (A2A), Agent Communication Protocol (ACP), and the engineering patterns required to build interoperable agentic systems on top of them at platform scale.
<br>
Strong hands-on knowledge of agent orchestration frameworks (LangGraph, Google ADK, LlamaIndex, Autogen, CrewAI, OpenAI Agents SDK, or equivalent), planning and reasoning loops, multi-agent coordination patterns, agent memory systems, and evaluation harnesses (RAGAS, OPIK, LangSmith, Promptfoo, or equivalent).
</li><li>Deep technical knowledge of LLM serving and inference architecture, including managed model APIs (Azure AI Foundry, AWS Bedrock, OpenAI, Anthropic, Google Vertex AI), provisioned throughput / PTUs, self-hosted open-weight models, GPU scheduling, vLLM / TGI / Triton, KV-cache management, batching strategies, and the cost-latency-quality trade-offs that drive model selection.
</li><li>Strong working expertise in LLM gateway and AI gateway architecture, including model routing, fallback and retry, prompt and semantic caching, rate limiting, tenant isolation, token accounting, and policy enforcement at the gateway boundary.
</li><li>Deep experience in retrieval and knowledge architecture, including vector databases (pgvector, Azure AI Search, Pinecone, Weaviate, Qdrant, or equivalent), hybrid retrieval, reranking, embeddings model selection, knowledge graphs (FIBO, RDF, OWL, SHACL, Neo4j, Apache Jena), and context engineering at scale.
<br>
Strong grounding in agent and workload identity, including non-human identity (NHI) governance, agent identity lifecycle, OAuth 2.1, OIDC, SPIFFE / SPIRE-style workload identity, mTLS, just-in-time credentialing, secret-less architectures, and integration with enterprise IAM (Microsoft Entra ID, Azure AD, PAM platforms).
</li><li>Deep proficiency in cloud-native platform engineering on Azure (preferred) and AWS, including Terraform, Kubernetes (AKS / EKS), Helm, service mesh (Istio, Linkerd), API gateways (APIM, Kong, Envoy), private networking, and policy-as-code (OPA, Azure Policy).
<br>
Strong programming proficiency in at least one of Python, Go, or Java, with active engagement in code reviews, design reviews, and platform-level engineering decisions.
</li><li>Strong Site Reliability Engineering background, including production on-call, incident leadership, post-mortem discipline, SLO and error-budget design, capacity planning, and observability tooling (Open Telemetry, Prometheus, Grafana, Datadog, or equivalent) tuned for non-deterministic AI workloads.
<br>
Working knowledge of integration patterns relevant to banking platforms, including event-driven architectures (Kafka, Event Hubs), API gateways, ESB, ISO 20022, payment rails, and core banking integration patterns.
</li><li>Strong grounding in security engineering for regulated industries, including OWASP LLM Top 10, prompt injection defence, model supply-chain security, secrets management, network segmentation, data residency, and audit logging.
<br>
Engineering Leadership &amp; Collaboration
</li><li>Demonstrated ability to operate effectively in a two-in-a-box model with another senior technical owner, including shared accountability, shared on-call, and shared decision-making.
</li><li>Track record of raising engineering standards across a platform team through standards, design reviews, documentation, and direct technical mentorship.
<br>
Strong written and verbal communication, with the ability to engage credibly with engineers, architects, risk and audit functions, hyperscaler and vendor technical teams, and senior business stakeholders.
<br>
Minimum Experience
</li><li>10+ years in software and platform engineering, with significant time spent at senior, staff, or principal engineering / architect level.
<br>
Demonstrated production ownership of at least one platform serving multiple internal or external consumers at enterprise scale, ideally including agentic or LLM workloads.
</li><li><p>Substantive experience in financial services, banking, or another comparably regulated industry.
<br>
Demonstrated SRE and on-call experience on a production platform with meaningful availability and operational requirements.
<br>
Track record of building, integrating, or operating LLM-based or agentic systems in production.
</p><p><b>Minimum Qualifications
</b></p></li><li><p>Bachelor's degree in computer science, Software Engineering, Electrical Engineering, or a related technical discipline.
</p><p><b>Preferred / Beneficial
</b></p></li><li>Master's degree (MSc / MTech / MEng) in Computer Science, Software Engineering, Distributed Systems, or a related discipline preferred.
</li><li>Relevant professional certifications in cloud engineering (Azure Solutions Architect Expert, Azure DevOps Engineer Expert, AWS DevOps Professional, AWS
</li><li>Solutions Architect Professional, Certified Kubernetes Administrator), security (CISSP, CCSP), or SRE considered an advantage.</li></ul></div></div><p></p>
<br><div><div>Responsibilities</div></div><div></div>
<br><div><div>Qualifications</div></div><div></div>
<br><div><div>About Us</div>
<div><div><b>About Us:<br>
</b></div><div></div><br>
<div>First Abu Dhabi Bank (FAB) is the largest bank in the UAE and one of the world's largest and safest financial institutions. We offer a comprehensive range of personal and private banking services, including credit cards, Islamic banking, investments, loans, and mortgages. Our commitment to excellence and innovation drives us to provide top-tier financial solutions to our clients.<br>
</div><div></div><br>
<div><b>Life at FAB:<br>
</b></div><div></div><br>
<div>Working at FAB means being part of a team of talented and passionate individuals with a shared vision to support the ambitions of our stakeholders to &quot;Grow Stronger.&quot; We embrace the needs of our customers across the globe with a sense of responsibility and confidence driven by extensive expertise that can only be delivered by an ambitious world-class organization<br>
</div><div></div><br>
<div><b>Career Development:<br>
</b></div><div></div><br>
<div>FAB offers unique career choices, a chance to innovate, craft solutions for the future, and express yourself in a performance-based culture that will unleash the best in you. Whether you are an experienced professional or just starting your career, FAB provides a range of learning and development initiatives to support all employees through training and skill development.<br>
</div><div></div><br>
<div><b>Our Values:<br>
</b></div><div></div><br>
<div>At FAB, we place our customers at the core of our activities, live our values each day in every way, celebrate achievements, and empower each other to deliver leading solutions. We have structured plans for the recruitment and career progression of Emirati talent to enable them to make a mark in the financial and banking sector both regionally and globaly that rewards your hard work and dedication.<br>
</div><div></div><br>
<div>Join our team and be part of a journey to shape the future of banking.</div></div></div><div></div>

Senior Engineer, Platform Engineering and Architecture

DICETEK LLC

<div><p><b>Description:</b></p><p>
We are looking for an experienced AI Engineer responsible for designing, developing, and deploying Generative AI and Agentic AI solutions that support enterprise-scale business use cases. This role includes building intelligent systems that integrate complex backend services and client-facing applications across web, mobile, and enterprise platforms.</p><p>
</p><p>The primary responsibility will be to design and develop AI-powered applications, autonomous agents, and multi-agent workflows, while coordinating with cross-functional teams across architecture, engineering, product, and business functions. Thus, a commitment to collaborative problem solving, sophisticated design, and product quality is essential.</p><p><b>
KEY ACCOUNTABILITIES:</b></p><ul><li>
Designing and building Generative AI applications using Large Language Models (LLMs)</li><li>
Developing Agentic AI solutions, including autonomous agents, multi-agent orchestration, and workflow-driven decision systems</li><li>
Building solutions using frameworks such as LangChain, LangGraph or similar agent frameworks</li><li>
Implementing RAG architecture with vector databases</li><li>
Knowledge of embeddings, vector DBs, and model evaluation.</li><li>
Implement various Context Engineering strategies to reduce Token Utilization &amp; Latency.</li><li>
Implement RAG Strategies to reduce retrieval latency and answer relevancy.</li><li>
Prompt engineering, tool calling, memory management, and agent orchestration</li><li>
Integrating AI services with enterprise APIs, middle ware, and backend systems</li><li>
Evaluated &amp; Improvise AI Agent Performance using several metrics</li><li>
Deploying scalable AI solutions on Azure / AWS cloud platforms</li><li>
Working with model evaluation, guardrails, observability, and AI governance</li></ul><p><b>
QUALIFICATIONS &amp; EXPERIENCE:</b></p><ul><li>
Bachelor&rsquo;s degree in computer science, Engineering, or a related field.</li><li>
Senior professional with around 10 years of experience.</li><li>
3+ years of relevant experience in AI Engineering</li><li>
Working experience in an agile software development environment with a good understanding of the principles of agile architecture. Strong collaborative mindset for collective decentralized decision making.</li><li>
Demonstrate strong technical skills with a deep understanding of modern architectural styles and practices such as Microservices, Containers, Cloud (AWS, Azure), APIs, Continuous Delivery, Event-driven architecture, Evolutionary architecture, etc., with a passion for hands on coding.</li><li>
Strong foundation knowledge of software architecture concepts, patterns, principles, and quality attributes. Ability to consistently apply them in real-world scenarios with a pragmatic, system thinking, and problem-solving mindset by analyzing architecture trade-offs for delivering high-quality, sustainable solution architecture.</li><li>
Proven leadership skills with a proactive, positive, and growth mindset. Ability to foster and motivate programmers for delivering with craftsmanship. Good personal skills to continuously engage and communicate with an egoless empathetic mindset.</li><li>
Experience and expertise in delivering architecture for large software solutions meeting critical business purposes. Ability to proactively discover technical debts and continuous improvement opportunities of existing live systems. Work closely with the product owner and enterprise architects to influence and prioritize technical backlog items.</li><li>
Strong proficiency in Python (NumPy, pandas, FastAPI, PyTorch/TensorFlow).</li><li>
Experience with Agent framework LangChain, Lang Graph.</li><li>
Architect end-to-end data indexing pipelines optimized for semantic search and RAG.</li><li>
Design resilient data ingestion frameworks that ensure high availability and low latency for vectorized datasets.</li><li>
Experience deploying and managing models via Amazon Bedrock, Azure OpenAI Service, and Google Vertex AI.</li><li>
Integration of pre-built AI APIs for Speech-to-Text, Computer Vision, and Natural Language Processing (NLP).</li><li>
Leveraging serverless architectures (e.g., AWS Lambda, Azure Functions) to trigger AI inference and data pre-processing.</li><li>
Experience working with CI/CD tools like Jenkins/Gitlab in Cloud Native environments.</li><li>
Experience in setting up pipeline for cloud based and on-prem based application with static code analysis, requirement tagging in Jira.</li><li>
Experience working with one or more DevOps tools &amp; config management tools.</li><li>
Experience in managing and deploying AI workloads in Kubernetes.</li><li>
Experience operating monitoring tools for traditional and cloud environments.</li><li>
Strong analytical mind for problem solving.</li></ul></div><p></p>

Senior AI Engineer

<div><div>Job Description</div>
<div>
<p><b>JOB SUMMARY / INTRODUCTION:
</b><br>
The Senior Automation Engineering manages test automation, engineering and devops practice across group IT which includes define, design and enhancements of test automation frameworks, design devops CICD pipeline solution, managing proof of concept for any new test automation tools into FAB landscape.
</p><p><b>KEY RESPONSIBILITIES<br>
</b><br>
</p><ul><li>Define, design, and implement enterprise grade test automation frameworks, maintaining and enhancing them for new requirements, and augmenting automation with AI-driven capabilities such as intelligent test generation, failure analysis, and test optimisation.
</li><li>Develop and embed best practices in Test Automation, DevOps, and CI/CD, incorporating AI-enabled validation and decisioning to support shift-left quality, security, and performance controls.
</li><li>Implement and support test automation, RPA, and AI-driven automation solutions across service lines, enabling scalable, reusable, and data-driven automation adoption across Group IT.
</li><li>Define and build automation platforms and tools to support Group IT automation initiatives, leveraging UiPath RPA and AI components (e.g., Document
</li><li>Understanding, OCR, machine-learning models) for intelligent process and test automation.
</li><li>Design and implement DevOps CI/CD solutions, integrating automated testing, RPA workflows, and AI-assisted validation into pipelines to enable end-to-end, touchless delivery.
</li><li>Identify, evaluate, and implement test automation, RPA, and AI-based tools, ensuring responsible and governed use of AI to enhance automation effectiveness, accuracy, and efficiency.
</li><li>Champion an automation-first and AI-enabled approach, embedding intelligent automation into delivery standards and GIT policies to reduce manual effort, improve quality, accelerate time-to-market, and drive measurable cost efficiencies.
</li><li>Define and design Test Automation framework which can be adopted by test automation teams.
</li><li>POCs for new automation tool and solutions.
</li><li>Support to test automation teams across testing Group IT.
</li><li>Design and implement Test Automation solutions that will support the quick time to market and reduction in manual test efforts.
</li><li>Design and implement Test Automation solutions.
</li><li>Experience in developing Automation tools using open-source technology like Selenium (BDD, Appium, Rest Assured, Karate framework, adoption of cloud-based mobile device farms).
</li><li>Proven experience in building automation solution that can be easily adopted by business and non-technical teams.
</li></ul><p>Addressing and implementing solution for complex issues involving (PDF automation, recording of test execution etc.) to ensure latest technology adoption and continuous improvement.
<br>
<br>
<b>REQUIREMENTS / QUALIFICATIONS<br>
</b><br>
</p><ul><li>A seasoned IT professional with 14+ years of diversified experience in Test Automation, Functional Testing and DevOps including GitLab CICD with core competencies in Selenium, Cucumber, Core Java, VB, Docker, Kubernetes, UFT, IBM tool and service Virtualization.
</li><li>Specialist in designing Test Automation framework in Selenium Java using BDD Cucumber for web mobile application.
</li><li>Comprehensive experience in creation and maintenance of GitLab repository, creating end-to-end pipeline architecture, setting up GitLab CI/CD and deployment to Kubernetes platform using helm chart, and on-premise deployment.
</li><li>Possesses strong hands-on experience in Web, Mobile, API and Desktop application development using VB and Java.
</li><li>Expertise with cloud platform providing mobile test solution like BrowserStack.
</li><li>Possesses strong hands-on experience in Service Virtualization using IBM RIT.
</li><li>Experience in co-ordination between Offshore and Onshore, multiple vendors in larger projects.
</li><li>In-depth business knowledge of Corporate Banking, Operations and Payment Systems.
</li><li>Strong decision-making capability under complex and strenuous conditions of large critical initiatives (e.g., merger, UAE workday changes, DR testing of bank merger).
</li><li>Highly adept at multi-tasking on several projects, mentoring team members and possessing excellent decision-making ability. Proactively evaluated risks and provided impact analysis along with alternate solutions to mitigate risks.
</li><li>Expert in identifying, developing and implementing QA processes &amp; procedures.
</li><li>Specialized in building competent teams and successful timely delivery of enterprise-level projects.
</li><li>Good experience in handling multiple projects simultaneously and interacting with different stakeholders.
</li><li>Good experience in handling large automation teams and expertise in delivering complex projects.
</li><li>Ensures data usage is always compliant with PCI/DDS regulation.
</li><li>Excellent communication skills with a capacity to present, discuss, and explain issues coherently and logically, in writing and verbally.
<br>
<br>
<b>Preferred / Beneficial
</b><br>
</li><li>Certified in AWS Cloud Practitioner, HashiCorp Terraform and IBM RFT tool.</li></ul></div></div>
<br><div><div>Responsibilities</div></div><div></div>
<br><div><div>Qualifications</div></div><div></div>
<br><div><div>About Us</div>
<div><div><b>About Us:<br>
</b></div><div></div><br>
<div>First Abu Dhabi Bank (FAB) is the largest bank in the UAE and one of the world's largest and safest financial institutions. We offer a comprehensive range of personal and private banking services, including credit cards, Islamic banking, investments, loans, and mortgages. Our commitment to excellence and innovation drives us to provide top-tier financial solutions to our clients.<br>
</div><div></div><br>
<div><b>Life at FAB:<br>
</b></div><div></div><br>
<div>Working at FAB means being part of a team of talented and passionate individuals with a shared vision to support the ambitions of our stakeholders to &quot;Grow Stronger.&quot; We embrace the needs of our customers across the globe with a sense of responsibility and confidence driven by extensive expertise that can only be delivered by an ambitious world-class organization<br>
</div><div></div><br>
<div><b>Career Development:<br>
</b></div><div></div><br>
<div>FAB offers unique career choices, a chance to innovate, craft solutions for the future, and express yourself in a performance-based culture that will unleash the best in you. Whether you are an experienced professional or just starting your career, FAB provides a range of learning and development initiatives to support all employees through training and skill development.<br>
</div><div></div><br>
<div><b>Our Values:<br>
</b></div><div></div><br>
<div>At FAB, we place our customers at the core of our activities, live our values each day in every way, celebrate achievements, and empower each other to deliver leading solutions. We have structured plans for the recruitment and career progression of Emirati talent to enable them to make a mark in the financial and banking sector both regionally and globaly that rewards your hard work and dedication.<br>
</div><div></div><br>
<div>Join our team and be part of a journey to shape the future of banking.</div></div></div><div></div>

Senior Engineer, QA Automation

<div><p>We are looking for an experienced AI Engineer responsible for designing, developing, and deploying Generative AI and Agentic AI solutions that support enterprise-scale business use cases. The role will build intelligent systems that integrate complex backend services and client-facing applications across web, mobile and enterprise platforms.</p><p>
The primary responsibility is to design and develop AI-powered applications, autonomous agents and multi-agent workflows while coordinating with cross-functional teams across architecture, engineering, product and business functions. A commitment to collaborative problem solving, sophisticated design and product quality is essential.</p><p>
This role requires strong hands-on engineering experience, practical working knowledge of modern agent frameworks, and the ability to deliver secure, scalable, observable and governed AI solutions in cloud-native environments.</p><p></p><p><b><br>
QUALIFICATIONS &amp; EXPERIENCE:
</b></p><p><b>Minimum Qualification</b></p><ul><li>Bachelor&rsquo;s degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence or a related discipline.</li><li>Relevant cloud, AI engineering, machine learning or architecture certifications are preferred.</li></ul><p></p><p><b><br>
Minimum Experience</b></p><ul><li>Senior professional with around 10 years of total software engineering, architecture, cloud or platform engineering experience.</li><li>Minimum 3+ years of relevant hands-on AI Engineering experience, including Generative AI and practical LLM-based application delivery.</li><li>Strong proficiency in Python, including NumPy, pandas, FastAPI and hands-on experience with PyTorch or TensorFlow.</li><li>Hands-on experience with LangChain and LangGraph; mandatory working experience with Microsoft Semantic Kernel and Microsoft AutoGen.</li><li>Experience implementing RAG using embeddings, vector databases, semantic search, retrieval optimization and model evaluation techniques.</li><li>Experience deploying and managing models using Amazon Bedrock, Azure OpenAI Service and Google Vertex AI.</li><li>Hands-on experience with microservices, containers, APIs, event-driven architecture, cloud-native services and evolutionary architecture practices.</li><li>Experience managing and deploying AI workloads on Kubernetes in cloud-native and/or hybrid environments.</li><li>Experience with CI/CD tools such as Jenkins or GitLab, DevOps toolchains, configuration management and cloud/on-prem deployment pipelines.</li><li>Experience setting up pipelines with static code analysis, requirement tagging in Jira, quality gates and release governance.</li><li>Experience operating monitoring tools for traditional infrastructure, cloud environments and AI-enabled business applications.</li><li>Strong hands-on problem-solving mindset with the ability to analyze trade-offs and deliver sustainable, secure and high-quality solutions.</li></ul><p></p><p><b><br>
Key Technical Skills</b></p><ul><li>Generative AI, Agentic AI, autonomous agents, multi-agent orchestration and workflow-based AI systems.</li><li>LLMs, embeddings, vector databases, RAG, semantic search, model evaluation, guardrails, observability and AI governance.</li><li>Semantic Kernel, AutoGen, LangChain, LangGraph and similar agent frameworks.</li><li>Python, FastAPI, PyTorch/TensorFlow, REST APIs, microservices, serverless functions and event-driven integration.</li><li>Azure, AWS, Kubernetes, containers, CI/CD, DevOps automation, monitoring and secure software delivery.</li></ul><p><b>
Behavioural / Leadership Skills</b></p><ul><li>Strong collaborative mindset for agile architecture and decentralized decision making.</li><li>Proactive, positive and growth-oriented leadership style with the ability to motivate engineers and foster craftsmanship.</li><li>Strong communication, stakeholder engagement and influencing skills across product, business, architecture and engineering teams.</li><li>Analytical, system-thinking and pragmatic problem-solving approach with commitment to product quality.</li></ul><p></p><p><b><br>
Skills:</b> Generative AI , Python , Kubernetes</p></div>

AI Engineer – Generative AI & Agentic AI

Greenfield Marine Technologies

<p>Head of Engineering</p><p><b>Location:</b> Abu Dhabi, UAE<br/><b>Experience:</b> 10&ndash;15+ years<br/><b>Employment Type:</b> Full-time</p><p>About the Role</p><p>We are looking for a <b>Head of Engineering</b> to lead our technology function and drive the development of scalable, secure, reliable, and high-performing SaaS and AI platforms for the maritime industry.</p><p>The role combines <b>technology leadership with hands-on technical oversight</b>, working closely with the Founder &amp; CEO, Product, AI, QA, Customer Success, and maritime domain teams.</p><p>The ideal candidate will have strong experience in <b>software architecture, engineering leadership, AWS/cloud infrastructure, DevOps, cybersecurity, AI, and enterprise software delivery</b>.</p><p>Key Responsibilities</p><ul><li>Define and execute the company's technology strategy and roadmap in alignment with business and product goals.</li><li>Lead and mentor <b>frontend, backend, mobile, AI, DevOps, and QA teams</b>, establishing clear ownership and engineering standards.</li><li>Own the architecture and scalability of web, mobile, backend, database, analytics, integrations, and AI platforms.</li><li>Review code, architecture, infrastructure, and technical decisions to ensure quality, security, maintainability, and scalability.</li><li>Drive predictable and timely product delivery, including sprint planning, development, testing, releases, and production support.</li><li><b>Own AWS infrastructure and DevOps</b>, including EC2, RDS, S3, CloudWatch, IAM, CI/CD, monitoring, backups, disaster recovery, and cloud cost optimisation.</li><li>Strengthen software quality through code reviews, automated testing, release processes, defect management, and reduction of technical debt.</li><li>Lead cybersecurity and data protection initiatives, including access control, encryption, vulnerability management, and readiness for <b>ISO 27001, SOC 2, GDPR, and VAPT</b>.</li><li>Guide AI and data initiatives, ensuring AI solutions are reliable, secure, scalable, and commercially useful.</li><li>Work directly with enterprise customers on technical requirements, integrations, deployments, security assessments, and complex technical issues.</li><li>Evaluate technology vendors and partners and ensure appropriate documentation, knowledge transfer, and ownership of technical assets.</li></ul><p>Technical Experience</p><p>Strong experience with several of the following:</p><p><b>React / Next.js | React Native | Node.js / Express | PostgreSQL | REST APIs | AWS | CI/CD | Docker | Git | Automated Testing | Sentry / Mixpanel | AI APIs / LLMs / RAG | Cybersecurity</b></p><p>Requirements</p><ul><li>Bachelor's or Master's degree in Computer Science, Software Engineering, IT, or a related field.</li><li><b>10&ndash;15+ years</b> of software engineering, technology management, or product development experience.</li><li><b>4&ndash;6+ years</b> leading engineering or technical teams.</li><li>Proven experience building and scaling <b>SaaS, enterprise, analytics, or operational platforms</b>.</li><li>Strong understanding of architecture, cloud, databases, APIs, DevOps, cybersecurity, and QA.</li><li>Experience managing multiple technical functions including web, mobile, backend, cloud, QA, and AI.</li><li>Strong experience working with enterprise customers and complex technical requirements.</li><li>Maritime, offshore, logistics, industrial, HSE, or operational technology experience is an advantage.</li><li>Experience with <b>ISO 27001, SOC 2, GDPR, VAPT, or enterprise security assessments</b> is highly desirable.</li></ul><p>What Success Looks Like</p><p>The successful candidate will improve:</p><ul><li>Engineering delivery and release predictability</li><li>Platform scalability, uptime, and performance</li><li>Code quality and automated test coverage</li><li>Production stability and incident resolution</li><li>Cybersecurity and compliance readiness</li><li>Cloud reliability and cost efficiency</li><li>Engineering team productivity and accountability</li><li>Customer satisfaction with technical delivery</li></ul><p>Why Join Us?</p><ul><li>Lead technology for a <b>fast-growing maritime AI and SaaS company</b>.</li><li>Work directly with leadership on strategic technology and product decisions.</li><li>Build technology serving leading maritime and offshore organisations.</li><li>Opportunity to make a direct impact on maritime <b>safety, efficiency, compliance, and sustainability</b>.</li><li>Significant leadership responsibility and long-term growth opportunity.</li></ul><p>How to Apply</p><p>Please submit your <b>CV</b>, relevant technology leadership experience, examples of SaaS/enterprise platforms you have built or scaled, team size/functions managed, notice period, current and expected compensation, and a brief overview of how you would assess and strengthen an existing technology platform in your first 90 days.</p><p>Application Question(s):</p><ul><li>How many years of experience do you have leading engineering/technology teams?</li><li>Please describe the SaaS/enterprise platforms you have built or scaled and their approximate scale (users, customers, or revenue, if applicable).</li><li>Which technical functions have you directly managed?</li><li>Notice period?</li><li>How would you assess and strengthen an existing technology platform during your first 90 days?</li><li>Visa Status, Visa Expiry Date?</li><li>Current Salary</li><li>Expected Salary</li></ul><p>Work Location: In person</p>

Head of Engineering

ai71

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  About AI71:
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 AI71 is an industry leader in artificial intelligence, delivering innovative solutions that empower developers, businesses and governments to solve complex challenges. AI71 builds secure, enterprise-ready applications powered by cutting-edge technology&mdash;tailored for knowledge workers and sector-specific needs. AI71 bridges the gap between advanced AI and real-world impact. Guided by a strong commitment to research and responsibility, we create transformative solutions that drive progress and empower communities.
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  The Role:
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 We are seeking a highly motivated and skilled DevOps Engineer to join our team. You&rsquo;ll play a crucial role in building, deploying, and maintaining scalable and reliable systems and infrastructure, working closely with development teams to ensure operational efficiency and smooth deployment pipelines.
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  What You'll Do:
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   Design, implement, and maintain CI/CD pipelines to streamline development workflows.
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   Build and manage scalable infrastructure for AI model deployment and lifecycle management.
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   Automate infrastructure provisioning and management using tools like Terraform, Ansible, or CloudFormation.
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   Optimize cloud-based and on-premises resources for scalability and cost efficiency.
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   Manage and fine-tune queuing systems and real-time streaming architectures.
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   Monitor and troubleshoot production systems to ensure uptime and performance.
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   Implement logging, monitoring, and alerting solutions using tools such as Prometheus, Grafana, ELK stack, etc.
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   Set up comprehensive monitoring for both system metrics and ML model performance.
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   Conduct root cause analyses and post-mortems to improve system reliability.
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   Collaborate with development and QA teams to deploy new features into production seamlessly.
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   Promote best practices in system architecture, security, and performance.
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   Participate in a rotating on-call schedule for production system support.
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   Ensure infrastructure complies with security and compliance standards (e.g., SOC2, ISO27001).
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   Securely manage secrets and credentials using tools like Vault or AWS Secrets Manager.
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  What You'll Bring:
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   Bachelor&rsquo;s degree in Computer Science, Engineering, or a related field (or equivalent experience).
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   Proficiency in at least one scripting language: Python, Bash, or Go.
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   Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud.
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   Skilled in containerization and orchestration with Docker and Kubernetes.
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   Experience using CI/CD tools such as Azure DevOps, Jenkins, GitLab CI/CD, or CircleCI.
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   Knowledge of monitoring and observability tools like Prometheus, Datadog, New Relic, Grafana, or PagerDuty.
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   Understanding of networking fundamentals including DNS, load balancing, and firewalls.
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   Familiarity with real-time streaming architectures for AI and data applications.
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  Great Pluses / Preferred Experience
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   Experience with Infrastructure as Code (IaC) tools like Terraform or Pulumi.
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   Understanding of service mesh technologies like Istio or Linkerd.
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   Familiarity with database scaling and administration, including VectorDBs, SQL, and NoSQL systems.
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   Previous experience in a high-traffic production environment.
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  Why AI71:
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    Mission-Driven Work:
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   Work on cutting-edge AI applications with a talented and passionate team, solving real-world challenges in critical sectors.
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    Unparalleled Opportunity:
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   This is a chance to innovate and solve real-world challenges using AI at a company with unique access to world-leading models and resources.
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    Career Growth:
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   We offer competitive compensation, benefits, and significant career growth opportunities as a foundational member of the team.
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    World-Class Environment:
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   Enjoy a flexible working environment and the latest tools &amp; technologies needed to do your best work.
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DevOps Engineer

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