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About the Role

The Senior AI Engineer leads the technical delivery of one or more AWA use cases end-to-end, from Agent Profile definition through to production UAT sign-off. You own architectural decisions within your use case domain: agent graph topology, confidence calibration, HITL threshold negotiation with the business, and the regression testing regime. You mentor AI Engineers and are the primary escalation point for complex LangGraph, LLM, and evaluation challenges, expected to identify failure modes before they reach production and to drive the adoption of new AWA capabilities across the use case portfolio.

Key Responsibilities

• Own technical delivery of one or more AWA use cases from discovery through production; define Agent Profile, Use Case Manifest, Data Manifest, and Tool Authorisation Matrix
• Design LangGraph agent graph topologies for complex multi-agent pipelines (Supervisor-Worker fan-out, parallel execution, state compression, 3-way match reconciliation)
• Lead AI Metric Baselines calibration: measure ECE, derive HITL routing thresholds empirically, present recommendations to business and risk teams
• Own and execute the full AWA IDP Test Strategy across Model/Prompt/Agent/Security, Adversarial, Integration, and UAT bands through to sign-off
• Maintain the Golden Dataset and Regression Dataset; configure CI/CD regression pipeline gates
• Mentor AI Engineers; conduct substantive technical code reviews of agent graphs, prompts, and MCP tool implementations
• Present model quality metrics, STP rates, and HITL rates to Ops leads and business owners with data-backed rationale
• Evaluate and prototype new AI capabilities (Azure AI Foundry models, new LangGraph features, RAG patterns) for the AWA accelerator catalogue

Essential Requirements

• 5+ years Python development; 2+ years in production AI/ML engineering
• Deep LangGraph or equivalent agentic framework experience: graph topology, state management, conditional edges, checkpoint-based recovery
• LLM evaluation expertise: F1 measurement against ground truth, Expected Calibration Error (ECE), hallucination detection, confidence calibration
• Prompt engineering at scale: versioned prompts, sensitivity analysis, few-shot dataset curation, PMS governance
• RAG architecture: hybrid retrieval (BM25 + vector), re-ranking, chunk citation, grounding verification
• Azure AI Foundry or equivalent LLM inference platform: PTU, PAYG, token budget management, APIM integration
• Workflow orchestration: Orkes Conductor or Temporal — HITL wait tasks, retry policies, compensating transactions
• CI/CD pipeline integration for ML: Azure DevOps, MLflow experiment tracking, model registry promotion

Advantageous

• Computer vision model deployment and evaluation (object detection — TPR/TNR/IoU)
• Azure AI Document Intelligence: form recogniser, custom models, layout analysis
• Kubernetes / AKS: workload identity, namespace isolation, KEDA autoscaling
• Apache Iceberg, DuckDB, and data contract patterns
• Banking domain knowledge: cheque clearing, trade finance, KYC, AML

Qualifications

• Bachelor's degree in Computer Science, AI/ML, or equivalent; Master's preferred
• Azure AI Engineer Associate or equivalent certification
• Demonstrable production AI deployments — case studies or public work highly valued

About the Role

The AI Engineer is the primary builder within the AWA AICoE. You will design, build, and test LangGraph agent graphs, LLM extraction pipelines, prompt management workflows, and MCP tool integrations that power AWA's use cases — starting with Intelligent Document Processing (IDP) for cheque clearing and expanding across ADCB's banking 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

• 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
• Build and maintain LLM-based entity extraction pipelines using Azure AI Foundry; implement structured output enforcement, per-field confidence scoring, and Pydantic validation against Use Case Manifest schemas
• Author, version, and govern prompts via the AWA Prompt Management System (PMS) with semantic versioning; run prompt sensitivity and correctness testing
• Develop and maintain the five core MCP tool servers (query_structured, retrieve_precedents, query_documents, checkpoint_state, observe) and extend for new use cases
• Execute Band 1 and Band 2 testing (Model/Prompt/Agent/Security/Adversarial) per the AWA IDP Test Strategy; maintain Golden and Regression Datasets
• Implement HITL interrupt() calls in LangGraph; configure Orkes Wait tasks; validate state persistence and checkpoint-based resumption
• Integrate Azure AI Content Safety, PII detection/tokenisation, prompt injection shielding, and output sanitisation at the AWA AI Gateway layer
• Implement cross-field validation rules (amount-words-vs-figures, date validity, MICR format, referential integrity) within LangGraph validation nodes

Essential Requirements

• 5+ years Python development — production-grade, not just scripting
• Hands-on experience with LangGraph, LangChain, or equivalent agentic AI frameworks
• Practical LLM prompt engineering: structured outputs, few-shot design, output schema enforcement
• Familiarity with Azure AI Foundry / OpenAI API or equivalent LLM API (Anthropic, Cohere)
• Understanding of agent design patterns: ReAct, self-reflection, tool use, HITL
• REST API development and consumption; JSON schema design
• Git version control; CI/CD pipeline awareness

Advantageous

• Experience with Orkes Conductor, Apache Airflow, or Temporal for workflow orchestration
• Azure AI Document Intelligence or equivalent OCR platform experience
• Computer vision model integration (object detection APIs)
• RAG architectures: chunking, vector indexing, Azure AI Search
• Azure platform familiarity: AKS, ADLS Gen2, Azure ML, Azure Monitor
• Pydantic, FastAPI, TypeScript/Node.js

Qualifications

• Bachelor's degree in Computer Science, AI/ML, Software Engineering, or related field
• Master's degree or equivalent research/industry experience advantageous
• Relevant Azure certifications (AI Engineer Associate, Developer Associate) advantageous

About the Role

We are looking for a Senior Platform Engineer to design, build, and scale Azure cloud and hybrid-cloud ecosystems from the ground up for a large Financial Enterprise. You will be responsible for creating a robust foundation for our application teams, with a specific focus on operationalizing AI services, maintaining rigorous security standards, and optimizing cloud spend through FinOps best practices.

Key Responsibilities

• Greenfield Infrastructure: Architect and deploy production-ready Azure environments from scratch using a landing zone approach
• AI Orchestration: Integrate and manage Azure AI services (OpenAI, AI Search, Document Intelligence, Content Safety) to support AI-driven application development
• Infrastructure as Code: Standardize all deployments using Terraform to ensure consistency and modularity
• API & Connectivity: Manage API lifecycles using Azure APIM and Kong, ensuring secure and performant communication between services
• FinOps & Monitoring: Proactively manage cloud costs by analyzing SKUs and implementing advanced monitoring/alerting to prevent budget overruns
• Automation: Design automated GitHub Workflows to enable seamless CI/CD for both infrastructure and application code

Technical Requirements

• Cloud: 5+ years experience with Azure Cloud Platform
• IaC: Expert-level Terraform skills
• AI Stack: Familiarity with Azure AI Foundry and OpenAI Service
• Networking: Expert knowledge of Network Architecture (VNETs, Peering, Firewalls, Private Links)
• APIs: Hands-on experience with Azure APIM or Kong
• Deployment Architecture: Proven ability to create professional Cloud Architecture Diagrams and provide Solutions Architecture guidance

About the Role

The Workflow Engineer designs and implements the business process orchestration layer of AWA using Orkes Conductor — the outer shell that holds LangGraph agent cognition together into coherent, durable, observable banking workflows. You translate complex banking process requirements (cheque clearing SLAs, HITL wait policies, compensating transaction rules, retry strategies) into Orkes workflow definitions. You are the primary integrator between the AWA AI Gateway, LangGraph agents, ICCS, Core Banking, and the Ops HITL interface.

Key Responsibilities

• Design and implement Orkes Conductor workflow definitions for all AWA use cases — task sequences, sub-workflow compositions, HITL Wait tasks, fork/join parallel execution, SLA-governed timeouts
• Configure Orkes Human Task definitions for HITL reviewer queue routing; implement HITL resume logic that correctly restores LangGraph checkpoint state after reviewer decision
• Design and test compensating workflows triggered on downstream failure (ICCS or Core Banking posting failure after IDP approval); ensure idempotency via awa_job_id deduplication
• Configure Orkes task retry policies (fixed, exponential backoff with jitter), circuit breakers, and dead-letter queue (DLQ) handling
• Design the interface between Orkes tasks and LangGraph agent invocations: passing awa_job_id, managing LangGraph as Orkes worker tasks, handling errors as task failures
• Ensure awa_job_id propagation through every task input/output; validate via integration tests in every downstream system record
• Configure Orkes workflow metrics export to Azure Monitor; build KQL queries for task failure rates, duration distribution, HITL queue depth, retry rate
• Lead workflow design for each new AWA use case: define the skeleton, agree task SLAs with business, design HITL routing policy, build workflow test suite

Essential Requirements

• 5+ years in workflow orchestration engineering: Orkes Conductor, Apache Conductor, Temporal, or Apache Airflow
• Strong understanding of distributed systems: idempotency, at-least-once delivery, eventual consistency, saga patterns
• Experience designing long-running durable workflows with human approval steps
• Python or Java for Orkes worker implementation
• REST API design: understanding of webhook patterns for async workflow resume
• JSON/YAML workflow definition authoring; schema validation

Advantageous

• Orkes Conductor specifically — Orkes Cloud, worker SDK, Human Task definitions
• LangGraph or LangChain awareness — agentic execution models that Orkes orchestrates
• Kafka consumer group management — for event-driven Orkes workflow triggers
• Azure Monitor, Log Analytics — for Orkes metric export and alerting
• Banking process knowledge — STP, clearing windows, exception handling flows

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or equivalent
• Demonstrable experience with production workflow orchestration systems managing thousands of daily workflow instances

About the Role

The DevOps Engineer owns the AWA platform's deployment, infrastructure-as-code, CI/CD, and operational reliability. You ensure that every AWA component — from AKS namespaces and KEDA autoscalers to ADLS Gen2 lifecycle policies and Azure Firewall allowlists — is deployed consistently, tested automatically, and operated reliably within ADCB's Azure UAE environment. You are the guardian of the AWA infrastructure: nothing is deployed manually; everything is reproducible from code.

Key Responsibilities

• Infrastructure as code: Own all AWA Azure infrastructure in Terraform/Bicep — AKS 5-namespace cluster, ADLS Gen2 with WORM, Azure AI Foundry APIM, Firewall allowlists, private endpoints, Key Vault, ACR, ExpressRoute peering
• CI/CD pipeline ownership: Design Azure DevOps pipelines for container build → ACR push → Notary v2 signing → AKS deployment; Terraform plan → policy check → apply; Agent Regression Testing gate on every PR
• AKS operations: Manage 5-namespace cluster — namespace isolation, Network Policies, PDBs, KEDA autoscaling on Kafka consumer lag, OPA Gatekeeper admission, Workload Identity bindings
• Container governance: Manage ACR, enforce Notary v2 image signing, configure vulnerability scanning, maintain approved-image ConfigMap used by OPA Gatekeeper
• Secret and certificate management: Own Azure Key Vault — access policies per managed identity, automatic TLS rotation, secret rotation schedules, audit of secret access
• Monitoring and alerting: Configure Azure Monitor alert rules and Log Analytics KQL queries for SLA breach, error rate spike, pod crash loop, token budget breach, Kafka consumer lag; maintain PagerDuty escalation
• Security posture: Implement Azure Policy assignments, Defender for Cloud recommendations, Firewall rule reviews, Private Endpoint configurations
• Disaster recovery: Maintain and test DR — failover to UAE South replica for ADLS Gen2, Azure AI Foundry PTU → PAYG → DR endpoint routing, Orkes cluster recovery, RTO/RPO validation

Essential Technical Skills

• 5+ years DevOps/Platform Engineering; 2+ years on Azure
• Terraform or Bicep — production IaC, not just templates
• Kubernetes / AKS: namespaces, RBAC, Network Policies, Helm charts, Kustomize
• Azure DevOps or GitHub Actions — multi-stage pipelines, approvals, environments
• Azure Monitor, Log Analytics, KQL query language
• Container ecosystem: Docker, ACR, image signing, admission control
• Azure networking: VNet, private endpoints, NSGs, Azure Firewall, ExpressRoute concepts
• KEDA (Kubernetes Event-Driven Autoscaling) or equivalent autoscaling experience

Advantageous

• Azure Key Vault, managed identity, Workload Identity for Kubernetes
• OPA Gatekeeper or Kyverno for Kubernetes policy enforcement
• Kafka / Azure Event Hubs — consumer group management, lag monitoring
• ADLS Gen2, WORM immutable storage, lifecycle management policies
• Azure AI Foundry / APIM — token quotas, rate limiting, backend routing
• Security tooling: Defender for Cloud, Sentinel, Notary v2

Qualifications

• Bachelor's degree in Computer Science, Systems Engineering, or equivalent
• Azure Administrator Associate (AZ-104) or DevOps Engineer Expert (AZ-400) strongly preferred
• Certified Kubernetes Administrator (CKA) advantageous

About the Role

We are seeking a Site Reliability Engineer to own the "Production Readiness" of our cloud-based AI solutions. This hybrid role combines automated software testing and Site Reliability Engineering (SRE). You will build the automated frameworks that validate our AI outputs and ensure the underlying Azure/AWS infrastructure is resilient, performant, and compliant with banking standards.

Key Responsibilities

• Resiliency Engineering (SRE): Implement "Chaos Engineering" and load testing to ensure web/mobile backends can handle banking-scale traffic. Maintain high availability through automated recovery scripts
• Automated Regression: Build CI/CD-integrated test suites using Python that validate both application logic and infrastructure state (IaC validation)
• Observability & SLIs: Define and monitor Service Level Indicators (SLIs) and Objectives (SLOs). Set up advanced alerting in Azure Monitor or AWS CloudWatch to catch performance degradation before users do
• Security & Compliance Testing: Automate security scans and compliance checks to ensure all AI data handling meets strict banking data residency and privacy protocols

Technical & Professional Requirements

• Automation Stack: High proficiency in Python (for AI testing) and framework automation (PyTest, Selenium, or Robot Framework)
• Cloud Infrastructure: Strong hands-on experience with Azure or AWS — networking, scaling, serverless reliability
• AI/ML Understanding: Understanding of Prompt Engineering and how to evaluate AI model outputs (RAG evaluation, ROUGE/BLEU scores, or custom LLM-benchmarks)
• Monitoring Tools: Experience with Grafana, Prometheus, or native cloud monitoring tools to build real-time reliability dashboards
• FinOps Awareness: Ability to identify "expensive" failing tests or inefficient cloud resource usage during testing

Recommended Skillset & Tools

• Languages: Python (Mandatory), Bash scripting
• Tools: GitHub Actions (CI/CD), Terraform (reading/validating), K6 or JMeter (Performance)
• AI Frameworks: DeepEval, Ragas, or LangSmith (for automated AI evaluation)

About the Role

The Full Stack Developer builds the human-facing surfaces of the AWA platform — the HITL reviewer interface, the AgentOps operational dashboard, and the internal AWA developer portals. You work at the boundary between the AWA AI pipeline and the people who use it: Ops reviewers, business analysts, bank customers, and the AWA engineering team itself. You translate complex agent state, confidence scores, and exception data into interfaces that enable fast, informed human decisions.

Key Responsibilities

• HITL reviewer interface: Design and build the Ops reviewer queue interface — document image display at native resolution, extracted field overlay with per-field confidence, exception reasons in plain language, Approve/Edit/Reject workflow with keyboard shortcuts optimised for reviewer throughput
• AgentOps dashboard: Build the AWA real-time operational dashboard consuming Azure Monitor metrics and Log Analytics: STP rate, HITL rate, rejection rate, document volume by use case, token consumption, latency P50/P95/P99, confidence distribution trends
• System integration: Build communication between AI systems and banking apps — deep-linked, session-managed, integrated with the AWA Conversation Orchestrator backend API
• Internal tooling and portals: Build the AWA Use Case Manifest authoring tool, the Prompt Management System (PMS) UI, and ground-truth annotation interface used by Ops for test data preparation
• API integration: Integrate frontend with AWA AI Gateway REST APIs, APIM-governed LLM endpoints, Azure Monitor query APIs, Orkes Conductor job status APIs
• Performance and accessibility: Ensure interfaces meet ADCB accessibility standards; optimise for low-bandwidth branch connections; implement loading states and graceful error handling for AI pipeline latency
• Design system: Build and maintain a consistent AWA design system (component library) used across all AWA-facing interfaces; align with ADCB brand standards

Essential Technical Skills

• 5+ years full stack development; strong React/TypeScript frontend
• REST API design and consumption; WebSocket / Server-Sent Events for real-time updates
• State management: Redux, Zustand, or React Query for complex async data flows
• Charting and data visualisation: Recharts, D3, or similar for operational dashboard metrics
• Node.js or Python backend (FastAPI / Express) for BFF (Backend for Frontend) patterns
• Authentication: OAuth2 / OIDC, Entra ID B2C for customer-facing channels
• Docker, Kubernetes basics — deploying frontend workloads to AKS

Advantageous

• Mobile development: React Native or native iOS/Android for Mobile Banking integration
• Image rendering and annotation: displaying high-resolution document scans with overlay layers
• Azure Static Web Apps, Azure Front Door, CDN configuration
• Streaming API responses: rendering LLM token streams in chat interfaces
• Familiarity with AI/ML concepts — enough to sensibly display confidence scores and model metrics

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or equivalent
• Portfolio of production applications — GitHub profile or deployed products will be reviewed

About the Role

Join our AI department as an AI Tester focused on validating AI/LLM-driven banking products. You will design test plans for prompt accuracy, hallucination mitigation and response completeness, automate user journeys, and ensure platform compliance with internal knowledge governance standards.

Responsibilities

• Develop test plans to validate prompt accuracy, hallucination mitigation, and response completeness
• Automate test scripts for user journeys within the AI tool
• Ensure platform compliance with internal knowledge governance standards
• Identify user experience issues, document defects, and create detailed reports on findings
• Maintain testing frameworks and tools, including automation

Skills

• Familiarity with automated testing tools (Selenium, Playwright, Cypress) and test management platforms (TestRail, Zephyr)
• Experience in AI/LLM output evaluation, especially for accuracy, relevance, and hallucination detection, is a strong plus
• Understanding of Agile/Scrum methodologies, CI/CD pipelines, and version control tools like Git
• Certification in ISTQB or similar QA frameworks is advantageous but not mandatory
• Excellent attention to detail and issue tracking via JIRA/TestRail

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field
• 2–5 years of experience in software quality assurance, ideally with exposure to AI/ML-based systems

About the Role

Design user journeys for chat, search, knowledge discovery, feedback, and admin workflows within our AI department's banking SaaS platform. Translate complex AI capabilities into clear, trusted product experiences.

Key Responsibilities

• Design user journeys for chat, search, knowledge discovery, feedback, and admin workflows
• Create wireframes, prototypes, and high-fidelity UI designs for web and mobile-responsive experiences
• Collaborate with product, engineering, and AI teams to translate user needs into clear product experiences
• Improve usability, accessibility, onboarding, and trust signals around AI-generated responses
• Conduct user research, usability testing, and iterate based on feedback and product analytics
• Maintain and evolve a consistent design system for an enterprise SaaS product

About the Role

Join our AI department as a Technical Business Analyst, bridging business needs and AI/ML technical delivery. You will identify AI opportunities, define scope, structure user stories, and drive the AI strategy alongside engineering and product teams.

Responsibilities

• Analyze business requirements and identify opportunities for AI/ML solutions
• Collaborate with stakeholders to define project scope and objectives
• Convert business requirements into structured user stories with clear descriptions, acceptance criteria, and definitions of done
• Continuously refine and prioritize user stories in the product backlog, ensuring readiness for development sprint cycles
• Conduct market research and competitive analysis to inform AI strategy
• Develop and present business cases for AI initiatives
• Monitor and evaluate the performance of AI solutions
• Stay current with advancements in AI/ML technologies and industry trends

Skills

• Strong understanding of AI/ML concepts and technologies
• Experience with business analysis tools and methodologies
• Excellent communication and collaboration skills
• Ability to analyze data and make data-driven decisions
• Strong problem-solving skills and attention to detail

Qualifications

• Bachelor's degree in Computer Science, Business, or a related field
• 5+ years of experience

About the Role

We are looking for a data-driven Scrum Master for the AI department at a large Financial Enterprise. Beyond managing individual squads, you will lead the Scrum of Scrums to synchronize multiple teams, manage cross-project dependencies, and provide a unified, "single source of truth" for senior leadership through expert Jira orchestration.

Key Responsibilities

• Program Orchestration: Lead the Scrum of Scrums (SoS) to align multiple AI squads, managing inter-team dependencies and resolving priority conflicts across the program
• Multi-Board Governance: Maintain high-integrity data across a shared Jira Space, ensuring distinct team boards accurately reflect separate priorities while rolling up into a consolidated program view
• Executive Visualization: Design custom Jira dashboards for senior stakeholders focusing on Sprint Goals, Burndown, Scope Creep (additions/deletions), and Quarterly velocity
• Flow & Capacity Management: Facilitate all Agile ceremonies and manage resource capacity allocation for sustainable delivery across workstreams
• Process Standardization: Establish a unified "Definition of Ready" and "Definition of Done" across the department to ensure consistent delivery quality in a regulated banking environment

Technical & Professional Requirements

• Scale & Complexity: Proven experience managing Scaled Agile environments or "Scrum of Scrums" for departments with multiple concurrent workstreams
• Jira/Confluence Mastery: Expert-level proficiency in JQL and Advanced Roadmaps to track dependencies across multiple boards within a single space
• Banking & AI Fluency: 5+ years in technical environments; ability to navigate the security and documentation rigors of the financial sector
• Metrics-Driven Leadership: Ability to translate fragmented team data into a cohesive "Program Health" report for non-technical leadership

Preferred Certifications

• PSM II/III or CSM
• SAFe (Scaled Agile Framework) or SMC (Scrum Master Certified) with a focus on scaling

About the Role

We are looking for an experienced PL/SQL Developer to design, develop, and optimize database procedures supporting our Loyalty Program and Co-branded Cards platforms. You will work on high-volume transaction processing systems, build/consume REST and SOAP APIs, and ensure efficient SQL execution across enterprise banking workloads.

Key Deliverables

• Design, develop, and optimize PL/SQL procedures, functions, and packages
• Performance tuning and efficient SQL execution across high-volume transactional workloads
• Integrate and consume REST / SOAP APIs to interface with internal and partner systems
• Support loyalty program flows — rewards earning, points accrual, redemption, and adjustment workflows
• Support co-branded card solutions — transaction processing, partner integrations, settlement reconciliation
• Troubleshoot production issues and provide L2/L3 production support
• Collaborate with application teams, partners, and operations on issue resolution

Requirements

• 7+ years of hands-on PL/SQL development experience
• Strong expertise in Oracle database, packages, triggers, and performance tuning
• Proven experience integrating REST and SOAP APIs from PL/SQL or middleware layers
• Domain experience in Loyalty / Rewards programs or Cards (Credit/Debit/Co-branded)
• Solid SQL optimisation skills — explain plans, indexing strategy, partitioning
• Experience with production support and incident troubleshooting in banking environments

Good to Have

• Exposure to PCI DSS compliance requirements
• Experience with card management systems and switch/clearing platforms
• Familiarity with Java / middleware integration (WebLogic, Mulesoft, Apache Camel)
• Knowledge of message queues (Kafka, IBM MQ) and event-driven patterns

About the Role

We are seeking a senior System Analyst to analyse, document, and validate business and functional requirements across enterprise banking systems. You will produce functional specifications, system flows, interface definitions, and data mappings, drive impact analysis for change requests, and ensure adherence to security/compliance/audit requirements including PCI DSS.

Key Deliverables

• Analyse, document, and validate business and functional requirements
• Produce functional specifications, system flows, interface definitions, and data mappings
• Conduct impact analysis for change requests across integrated banking systems
• Support solution design and integration with IT teams, architects, and partner vendors
• Support SIT / UAT / Regression testing cycles and drive defect triage to resolution
• Coordinate with external vendors and third parties on integration and delivery
• Ensure adherence to security, compliance, and audit requirements (PCI DSS, internal banking standards)

Requirements

• 10+ years of experience as a System Analyst / Technical BA in banking or financial services
• Strong functional documentation skills — specs, flows, interface contracts, data mappings
• Working knowledge of PCI DSS and other banking security/compliance standards
• Hands-on SIT/UAT/Regression coordination and defect management experience
• Proven track record of vendor and third-party coordination in regulated environments
• Strong stakeholder communication — business owners, architects, vendors, audit

Good to Have

• Domain exposure to Cards, Loyalty, ATM, or Core Banking platforms
• JIRA / Confluence proficiency for requirement traceability
• Experience with API contracts (REST / SOAP) and integration design

About the Role

We are looking for a senior IT Test Engineer to own quality, SLA, and KPI management across ATM and Cards platforms. You will lead vendor follow-ups on issue resolution, coordinate hardening and patching cycles, support project teams on UAT, and drive communication on critical customer-impacting issues.

Key Deliverables

• SLA & KPI management across ATM and Cards platforms
• Follow up with vendors and external partners on issues and resolution timelines
• Coordinate internal teams for hardening / patching / upgrade and maintenance cycles
• Troubleshoot critical issues and communicate customer-impacting incidents clearly to stakeholders
• Support project team delivery work — testing strategy, environment readiness, regression coverage
• Provide UAT support for assigned systems and drive defect closure

Requirements

• 10+ years of experience in IT testing / quality engineering with strong ATM and Cards platform exposure
• Solid SLA / KPI management background — vendor scorecards, MTTR, MTBF reporting
• Experience coordinating hardening, patching, and platform upgrades in a 24x7 environment
• Strong knowledge of card transaction flows, switch integrations, and ATM monitoring
• Familiarity with PCI / security standards relevant to ATM and Cards
• Proven track record of vendor management and incident communication at customer-impact level

Good to Have

• Exposure to ATM monitoring tools and EFT switch platforms
• Test automation experience for back-office and switch systems
• ITIL certification or equivalent service management background

About the Role

We are looking for a Senior AI Engineer / Agentic AI Engineer with proven experience delivering enterprise-scale AI solutions in Banking or Financial Services. The ideal candidate will have strong hands-on expertise in Agentic AI systems, Generative AI pipelines, and production-grade Conversational AI / RAG platforms, particularly on Microsoft Azure. You will work on high-impact banking use cases such as Conversational AI, Document Intelligence, Agentic Automation, and Multimodal AI systems serving large user bases.

Key Responsibilities

• Design and implement Agentic AI architectures for enterprise banking applications
• Build scalable Generative AI / RAG pipelines using Azure OpenAI and Azure AI Search
• Deliver production-grade AI systems with high availability, security, and performance
• Develop multimodal and multilingual AI solutions (Text & Vision – English / Arabic)
• Implement document intelligence pipelines using Azure AI Document Intelligence
• Build computer vision workflows using OpenCV
• Develop and expose REST APIs (FastAPI) and deploy using Docker & Azure Containers
• Design embedding, vector search, and hybrid retrieval strategies
• Integrate with Azure Cosmos DB / Document DB
• Implement CI/CD pipelines and Git-based workflows

Mandatory Requirements

• 6+ years hands-on experience in AI / ML / Generative AI / Agentic AI
• Proven experience delivering AI solutions in Banking / Financial Services
• Strong programming skills in Python and SQL
• Expertise in Microsoft Azure AI stack: Azure OpenAI, Azure AI Search, Azure AI Document Intelligence, Azure Vision, Azure AI Foundry
• Experience with LangChain / LangGraph (Agentic frameworks)
• Strong Prompt Engineering skills
• Experience in Computer Vision (OpenCV)
• API development using FastAPI
• Hands-on with Git, Docker, Azure Container Services
• Experience with Azure Cosmos DB / Document DB
• Experience in CI/CD pipelines

Good to Have

• Experience with open-source AI frameworks (YOLO, Deep Learning, NLP)
• Familiarity with Semantic Kernel / Microsoft Agentic Framework
• Knowledge of LLM evaluation frameworks (RAG evaluation, benchmarks)
• Experience with MCP (Model Context Protocol)
• Exposure to Orkes or similar agentic workflow tools
• Experience with Streamlit / Flask for rapid prototyping
• Microsoft Certified: Azure AI Engineer (AI-102)

About the Role

We need a candidate who can handle end-to-end solution design, not just individual components. You will engage with application teams, gather requirements clearly, and translate business needs into scalable, secure, and cost-effective architectures. Design for high availability and disaster recovery with clear understanding of RTO/RPO, and balance performance, scalability, availability, and cost with clear trade-offs.

Key Responsibilities

• Handle end-to-end solution design, not just individual components
• Engage with application teams and gather requirements clearly
• Translate business needs into scalable, secure, and cost-effective architectures
• Design for high availability and disaster recovery, with clear understanding of RTO/RPO
• Define and explain security across all layers (application, network, data)
• Balance performance, scalability, availability, and cost with clear trade-offs
• Work across multiple projects and support different teams
• Present and defend architecture decisions in front of stakeholders or review boards

Technical Requirements

• Minimum 8 years of hands-on experience designing cloud-native and distributed architectures on AWS
• High availability and multi-region / multi-zone architecture patterns
• Disaster recovery strategies and backup approaches
• Security best practices across identity, network, and data layers
• Application architecture patterns (e.g., 3-tier, microservices)
• Scalability and performance optimization approaches
• Infrastructure automation and deployment practices
• CI/CD and environment management across dev, test, and production
• Container-based architectures and orchestration concepts
• Monitoring, logging, and observability practices
• Networking fundamentals (segmentation, routing, access control)

Nice to Have

• Exposure to AI/ML workloads or high-performance environments

What We're Looking For

Important Note: The client is not focused on certifications or tool names. They are assessing structured thinking, real production experience, ability to explain decisions clearly, and end-to-end ownership of architecture. We prioritize candidates who can clearly explain real projects end-to-end, have strong practical experience (not just theoretical knowledge), and demonstrate good communication and structured thinking.

About the Role

Looking to take your data science career to the next level? We're on the hunt for a seasoned Data Scientist with strong experience in the banking domain to join our team! If you're passionate about solving complex problems and making a real impact in financial analytics, we'd love to connect!

What We're Looking For

• 6+ years of hands-on experience in Data Science
• Strong exposure to the banking/financial services sector
• Proven experience in risk-based projects: Credit Risk Modeling, Loan Analytics, Scoring Platforms
• Deep expertise in machine learning, statistical modeling, and data analysis
• Strong problem-solving mindset with the ability to translate data into actionable insights

What You'll Do

• Build and deploy advanced models for risk and decisioning
• Work on high-impact projects influencing financial outcomes
• Collaborate with cross-functional teams to drive data-driven strategies

About the Role

Design, implement, and maintain CI/CD pipelines, automate infrastructure provisioning, and ensure reliable application delivery across AWS environments. Work on enterprise-grade cloud infrastructure with full visa sponsorship.

Key Responsibilities

• Design and implement end-to-end CI/CD pipelines using Jenkins, GitLab CI, GitHub Actions, or AWS CodePipeline
• Provision and manage AWS infrastructure using Infrastructure as Code (Terraform, CloudFormation)
• Configure and maintain containerized environments using Docker, Amazon ECS, EKS, or Fargate
• Set up comprehensive monitoring, logging, and alerting using CloudWatch, ELK Stack, Prometheus, Grafana
• Manage core AWS services: EC2, S3, RDS, Aurora, Lambda, API Gateway, Route53, IAM, VPC

Requirements

• Minimum 6 years of hands-on experience with AWS cloud services
• CI/CD Tools: Jenkins, GitLab CI, GitHub Actions, AWS CodePipeline, ArgoCD
• Infrastructure as Code: Terraform (strongly preferred), CloudFormation, AWS CDK
• Containers & Orchestration: Docker, Kubernetes (EKS), Amazon ECS
• Scripting: Python, Bash, PowerShell