GenAI Engineer (Banking/Financial)

Experience: 8+ years in software or data engineering, including 2+ on LLM applications and 3+ in banking or regulated financial services

Must-have skills

Banking and controls

· Building software in regulated environments: authentication, entitlements, audit logging and data privacy.

· Applying row-level access and human review steps to AI outputs.

Generative AI engineering

• LLM applications beyond proof of concept: RAG, embeddings, vector stores and structured outputs.

• Text-to-SQL over a semantic layer; conversational retrieval of reports and KPIs.

• Agent frameworks such as LangGraph or LlamaIndex.

• Evaluation: accuracy, SQL correctness, hallucination testing and guardrails, automated in CI/CD.

• Code parsing and lineage extraction for SQL, PL/SQL, SAS and Python (e.g. sqlglot, ANTLR).

Software and data engineering

• Strong Python and SQL.

• Working with enterprise data at warehouse scale.

• Git, CI/CD and MLflow.

Good-to-have skills

• Enterprise LLM platforms: Azure OpenAI, AWS Bedrock or Vertex AI.

• Databricks Mosaic AI or Genie.

• Visualisation libraries (Plotly, ECharts, Vega) and Qlik or Power BI APIs.

Certifications (preferred): Databricks Generative AI Engineer Associate; Azure AI Engineer; AWS ML Specialty.