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Lead the design and implementation of security controls in banking environments, ensuring compliance and technical integrity across systems while mentoring other engineers.

The role involves managing cloud security vulnerabilities for a banking client, overseeing vulnerability management, collaborating with engineering teams, and producing risk reports.

Design and implement scalable conceptual, logical, and physical data models and semantic layers for Lakehouse/Medallion architectures. Build knowledge graphs and ontologies, integrate with metadata/lineage tools, ensure schema evolution and performance, and collaborate with architects, engineers and stakeholders to enable self-service analytics and data discovery.

Own end-to-end data platform verification: design and run automated functional, integration, and E2E tests, API/contract testing, source-to-target reconciliation, Soda Core checks across Bronze/Silver/Gold, monitor alerts and perform root-cause analysis, and embed automated validation into live data flows while collaborating with data engineering squads.

Lead design and implementation of secure, compliant multi‑cloud (Azure/AWS) architectures for AI and banking platforms. Own HLDs/LLDs, cloud governance, FinOps, CI/CD pipeline security, zero‑trust networking, and mentor engineering squads while advising senior stakeholders on architecture and regulatory risk.

Lead design and implementation of end-to-end test automation and validation frameworks for web UIs, microservice APIs, Kafka streaming pipelines, and Generative AI/LLM outputs. Build Playwright-based suites, API tests, prompt/ground-truth datasets, integrate tests into CI/CD, and collaborate with AI engineers and DevOps to ensure accuracy, safety, and reliability of enterprise AI systems.

Own and automate the AWA platform deployment architecture in Azure: IaC (Terraform/Bicep), AKS cluster and namespace management, CI/CD pipelines, image signing, security policies, monitoring (KQL/Azure Monitor), private connectivity, Key Vault secret management, and automated DR to meet RTO/RPO targets.

Build and maintain human-facing surfaces for the Agentic Workflow Automation platform, including HITL reviewer UI, AgentOps dashboards, internal tooling, and design system. Integrate real-time streams, Azure monitoring, secure APIs, authentication, containerized deployments (AKS), and optimise performance and accessibility for enterprise banking workflows.

Design, deploy, and operate secure, scalable end-to-end AI and Generative AI systems across cloud and on-prem environments. Build APIs, integrate foundation and open-source models, implement MLOps pipelines, monitoring, and FinOps, optimize inference cost, and work with vector databases, embedding retrieval, and large-scale data processing for enterprise clients (banking/financial services).

Lead delivery of complex AI, data science, and banking projects end-to-end. Combine Agile and traditional methodologies, manage budgets >$1M, mitigate AI-specific risks, run Scrum ceremonies, align stakeholders, and report KPIs for executive audiences.