Design and build AI-enabled applications for DB Intelligence, including user-facing workflows, APIs, microservices, orchestration
components and data integration layers.
Develop modern React / TypeScript front ends with reusable components, strong API integration and user experiences that
support explainable AI-assisted workflows or
Build Python services for AI/ML integration, model orchestration, RAG, agentic workflows, data processing, evaluation pipelines
and automation or
Develop and integrate Java / Spring Boot microservices for enterprise backend capabilities, business rules, workflow
orchestration and secure service-to-service communication.
Work with structured and unstructured data sources, including internal systems, documents, market/event data, portfolio data and
enterprise knowledge sources.
Contribute to AI architectures using LLM APIs, prompt orchestration, embeddings, vector search, RAG, model evaluation,
guardrails and human-in-the-loop review.
Engineer solutions that support scenario analysis, event-driven intelligence, impact assessment, portfolio/risk insight generation
and decision support.
Apply strong engineering discipline: clean code, automated testing, CI/CD, code reviews, observability, performance tuning,
resilience and production support readiness.
Implement controls for data privacy, entitlement management, audit logging, explainability, traceability, model output monitoring
and responsible AI usage.
Provide senior technical contribution, design leadership, mentoring and reusable engineering patterns across the programme.
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