AI Platform & Data Engineer - Databricks / MLOps

Candidates must be authorized to work in the US without current or future sponsorship (including H-1B transfer or OPT/STEM OPT). Work authorization will be verified as part of the hiring process.The following information aims to provide potential candidates with a better understanding of the requirements for this role.About the RoleJCW is partnering with a global financial institution to hire an AI Platform & Data Engineer to build and run the data foundation behind its enterprise GenAI platform. AI is only as good as the data feeding it, and this role owns that layer. You will build the Databricks pipelines that prepare, govern and deliver trusted data to AI models, RAG applications and agents. You will also make sure those AI systems run reliably in production. You will work closely with Architecture, Technology, Data and business stakeholders, and partner with Azure, Databricks and other infrastructure providers. This is a hands-on engineering seat for someone who is strong in data engineering on Databricks and has worked on getting AI into production.What You'll DoBuild and maintain scalable data pipelines on Databricks and Azure that ingest, clean, transform and deliver data for AI and GenAI use casesPrepare data for RAG and AI applications, including document ingestion, chunking, embeddings and managing vector indexes with Databricks Vector SearchOwn data quality across the AI platform, defining quality checks and monitoring for data drift, freshness and completenessImplement end-to-end data lineage, versioning and governance across data, prompts, models and responses using Unity Catalog and MLflow, delivering audit-ready artifacts for regulatory reviewBuild CI/CD and infrastructure-as-code using Databricks Asset Bundles to promote data pipelines, models and AI workflows across DEV/QA/REL/PRODSupport the MLOps/LLMOps lifecycle, including model deployment, monitoring for performance and grounding, and cost visibilityApply security and privacy controls to sensitive data used in AI, including access management, secrets management and protection of data and embeddingsSupport day-2 operations through runbooks, incident response and SLAs, and help educate wider teams on data and AI platform best practicesWhat We're Looking ForBachelor's degree in Computer Science, Data Engineering, Data Science or a related field5+ years of hands-on data engineering experience, with recent work supporting AI/ML or GenAI use cases in productionStrong Python, PySpark and SQL skillsDeep hands-on Databricks experience, including Delta Lake, Unity Catalog, Workflows and Asset Bundles, along with Azure data servicesExperience preparing data for GenAI, such as document processing, chunking, embeddings and vector databases (e.g., Databricks Vector Search, Azure AI Search)Hands-on experience with MLflow and MLOps/LLMOps practicesExperience building data quality checks, monitoring and lineage in a production environmentExperience with CI/CD, infrastructure-as-code and containerizationFamiliarity with data governance and security controls in a regulated environment, ideally financial servicesExcellent communication skills, with the ability to partner with technical and non-technical stakeholdersThe DetailsThis role is based in Charlotte, NC, with 2 days per week on site. Candidates looking to relocate to Charlotte are welcome to apply, though relocation assistance is not provided. Applicants must be US Citizens or Green Card holders; visa sponsorship is not available.JCW is proud to be an equal opportunity recruiter. xhyhwjd We are committed to fostering an inclusive recruitment process and ensuring equal consideration for all applicants regardless of gender, age, disability, religion, sexual orientation, marital status, or race.