Lead Software Engineer - Python, Full Stack / AI
On-siteJersey City, New Jersey, United States
Job Summary
Lead end-to-end data platform development for Capital, Liquidity, and Balance sheet management using React/TypeScript UIs and Python servers. Deliver data pipelines and ETL on Databricks and Snowflake while executing software solutions, design, and technical troubleshooting. Supervise LLM-assisted and agent-driven development, ensuring models like Claude and ChatGPT function as controlled, versioned engineering artifacts that support determinism and traceability in regulated environments. Drive team adoption of AI-assisted code review, refactoring, and test acceleration to improve delivery speed and operational outcomes. Establish best practices for prompt-driven design, secure coding, and automated testing within the Software Development Life Cycle.
Required Qualifications
- Formal training or certification on software engineering concepts
- 5+ years of applied experience
- Strong Python skills
- Familiarity with agentic development (ADLC)
- Demonstrated Engineering leadership
- Architecture skills
- Stakeholder management skills
- Database design and modeling on modern data platforms (Databricks, snowflake)
- Hands on experience in co-pilot or Claude-code to design and deliver end-to-end applications
- Working understanding of multi public cloud
- Exposure to AWS Cloud
- Experience in developing, debugging, and maintaining code in a large corporate environment
- Experience with one or more modern programming languages
- Experience with database querying languages
- Experience in Risk and Pnl in Markets
- Understanding of agile methodologies such as CI/CD
- Understanding of Application Resiliency
- Understanding of Security
- Demonstrated experience leading effective use of approved AI-assisted software development tools
- Ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows
- Experience with data sensitivity considerations
- Experience with secure handling of inputs/outputs
- Experience with adherence to resiliency and security expectations
- Experience coaching engineers on safe, compliant adoption within delivery practices
Desired Qualifications
- Experience in Risk and Pnl in Markets
- Knowledge of Financial Markets and Products (Fixed Income, Derivatives)
- Knowledge of Treasury concepts
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