Deep Light AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations.
The GenAI Platform Lead is a highly technical role dedicated to the design, deployment, and management of scalable AI infrastructure on Azure. You will be responsible for creating the backbone of the Bank’s AI initiatives, integrating Machine Learning Operations (MLOps), containerization, and robust data engineering practices. By leveraging Infrastructure as Code (Terraform) and advanced cloud-native services, you will ensure that AI applications are secure, high-performing, and compliant with global banking standards.
This role bridges the gap between raw data and production-ready AI, providing the platforms that allow Data Scientists and Engineers to deploy impactful solutions at scale.
As the GenAI Platform Lead, your responsibilities will include:
- Building and managing scalable AI environments using Azure Virtual Machines, Azure Kubernetes Service (AKS), and Azure Functions.
- Developing and maintaining CI/CD pipelines for automated model deployment, versioning (MLflow), and monitoring using Azure Dev Ops and Git Hub Actions.
- Leading "Infrastructure as Code" (IaC) initiatives using Terraform to automate resource provisioning and ensure environment consistency.
- Configuring secure networking (Firewalls, VNETs, NSGs) and manage access control through Azure RBAC, Key Vault, and Azure Policy.
- Designing and implementing data pipelines using Azure Data Factory, Databricks, and Synapse Analytics to facilitate real-time data ingestion and warehousing.
- Tracking model performance, data drift, and infrastructure costs using Azure Monitor, Application Insights, and Cost Management tools.
- Organizing and supervising team activities, ensuring targets are met in line with ADCB’s policies and continuous improvement initiatives.
- Supporting, Coaching and Mentoring more junior members of the team, when required
- Additional responsibilities on occasion, on management request
As an AI consultancy, our greatest asset is the expertise of our people.
While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deep Light.
We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills.
You will be the face of our firm, tasked with building trust, articulating the "why" behind your technical decisions, and effectively "selling" your vision to high-level stakeholders.
If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in.
What we need from you:- Minimum of 5 years in designing and deploying AI/ML solutions on Azure.
- Bachelor’s degree in Computer Science, AI, Software Engineering, Statistics, or a related quantitative field.
- Azure Certifications (e.g., Azure Solutions Architect, Azure AI Engineer, or Azure Administrator) are highly preferred.
- Proven track record of managing secure, compliant systems in a high-stakes environment (e.g., Banking or Finance).
- Deep proficiency in Azure infrastructure management, including Subscriptions, Resource Groups, and Blueprints.
- Hands-on experience building and managing container images via Azure Container Registry (ACR) and deploying via AKS or Container Apps.
- Advanced expertise in Terraform for automating complex cloud architectures.
- Strong grasp of secure cloud networking and secret management (Azure Key Vault).
- Proficient in Azure Dev Ops, Git Hub, and data processing frameworks like Apache Spark.
- Familiarity with AWS services (Sage Maker, S3, Cloud Watch) for cross-cloud or hybrid deployment scenarios.
- Ability to optimize cloud spend while maintaining high availability and performance.
- Unde…
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