Senior Lead Python/PySpark Engineer for AI‑Driven Reg Reporting

Aumni; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

J.P. Morgan is seeking a Senior Lead Software Engineer within the Corporate and Investment Bank Payments Technology team. You will push the envelope to enhance, build, and deliver secure, scalable technology products in a dynamic, agile environment.

You will lead end-to-end delivery for Regulatory Reporting initiatives, mentor teams, and advocate responsible AI use across engineering workflows, including integration with cloud-native data platforms.

Qualifications

• Bachelor's Degree in Computer Science/Information Systems/Engineering or related discipline.
• 8+ years of hands-on software development experience delivering system design and operations.
• Advanced in Python.
• Experience leading use of AI-assisted development tools and validating AI outputs.

Responsibilities

• Provide technical guidance to teams, contractors, and vendors.
• Own end-to-end delivery for Regulatory Reporting initiatives as a senior individual contributor.
• Develop secure, high-quality production code and review code written by others.
• Drive adoption of AI-assisted engineering practices with measurable validation and security checks.
• Build and optimize data pipelines and reporting workloads using Databricks Lakehouse (Delta Lake, Spark SQL, PySpark).
• Influence product design, application functionality, and technical operations; collaborate with stakeholders on regulatory submissions.

Skills

Python

AI-assisted tooling

Independent problem solving

Education

Bachelor's degree in CS/IS/Engineering

Tools

PySpark

Databricks

Spark SQL

AWS

Job description

J.P. Morgan is seeking a Senior Lead Software Engineer within the Corporate and Investment Bank Payments Technology team. You will push the envelope to enhance, build, and deliver secure, scalable technology products in a dynamic, agile environment.

You will lead end-to-end delivery for Regulatory Reporting initiatives, mentor teams, and advocate responsible AI use across engineering workflows, including integration with cloud-native data platforms.