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Tier-1 brand, mid-level generalist data role with broad skills attracts many qualified applicants.
Requires regulated financial KYC, enterprise data platform and LLM experience, limiting cross-industry transferability.
Many mandatory enterprise-scale data, cloud and LLM experience requirements create strict shortlisting filters.
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Develop and maintain secure, scalable production code for data-intensive applications supporting Global KYC and Risk Assessment Data Platform.
Lead architectural design and establish engineering standards for AI-driven, LLM-based applications and multi-agent workflows in regulated environments.
Mentor engineers and drive adoption of advanced technical methods, collaborating across teams to deliver trusted risk management platforms.
5+ years of applied experience with formal training or certification in software engineering.
Expertise in Python and/or Java with hands-on experience in system design, development, testing, and operational stability at enterprise scale.
Practical experience designing and deploying production AI/ML systems, including LLM-based applications with multi-agent architectures in regulated environments.
Practical cloud-native experience with AWS, Azure, or GCP, plus experience in large-scale data processing and data governance.
Experienced in developing and governing AI systems with multi-agent workflows and human-in-the-loop controls within a regulated financial environment.
Strong background in large-scale data engineering including microservices, Kafka, observability tools, and orchestration frameworks.
Proficient in communicating complex technical concepts and architectural decisions to senior leaders and executives.