Applied AI ML Associate Senior-Data Engineer

Builds and maintains scalable data pipelines and feature stores supporting the team's AI/ML products, from source systems through to production

Implements data quality, validation, and monitoring so downstream models and applications can trust their inputs

Structures and models data for retrieval-augmented generation, feature engineering, and analytics workloads

Partners with AI engineers to productionise data flows for agentic AI and ML use cases

Applies data access, privacy, and residency controls to firm-wide and cross-border regulatory standards

Contributes to design discussions and code reviews, growing towards greater technical ownership

Uses AI coding tools (e.g., Claude Code, GitHub Copilot) as part of day-to-day development

Formal training or certification on software or data engineering concepts and 3+ years applied experience

Proficiency in Python and SQL, and familiarity with modern software engineering practices (testing, code review, version control)

Hands-on experience building and maintaining data pipelines and ETL/ELT workflows

Exposure to distributed data processing and platforms such as Spark / Databricks

Working knowledge of cloud-native data services, containerisation, and CI/CD

Understanding of data modelling and warehousing concepts

Ability to communicate clearly with engineers, data scientists, and stakeholders

BSc in Computer Science, Data Engineering, or a related quantitative field

Industry-recognised data engineering certification (e.g., AWS Certified Data Engineer - Associate (DEA-C01), or similar)

Exposure to data foundations for ML / LLM workloads (feature stores, vector stores, RAG pipelines)

Exposure to financial services, particularly wealth, private banking, or asset management

Familiarity with data governance, lineage, and privacy tooling

Familiarity with JPM-internal data and AI/ML infrastructure for internal candidates