Software Engineer III- Python & AI

Overview

In this role, you design and implement robust Python-based financial control systems supporting IRIS, a critical revaluation infrastructure. You collaborate with asset class and platform teams to build scalable, secure solutions that ensure balance sheet integrity and regulatory compliance. You’ll work with cutting-edge tech to simplify complex valuation and risk processes, contributing meaningfully to a mission-driven finance technology organization. This is a hands-on, impact-focused engineer role with a strong emphasis on quality and audit readiness.

Responsibilities

• Design and develop Python applications in a large mono-repo with proprietary workflows
• Create graph-based data pipelines for valuation adjustments and risk analysis
• Implement independent price verification and valuation workflows across asset classes
• Develop consensus pricing integrating external market data providers
• Configure distributed compute, job scheduling, analytics integrations, and cloud storage pipelines
• Write and maintain unit, integration, and parameterized tests
• Investigate and remediate security vulnerabilities and support audit remediation
• Operate with an audit-first approach on production systems
• Design and maintain AI developer tooling including prompt engineering and LLM-assisted code generation

Key requirements

• Proficiency in Python 3 with typing, context managers, generators, and functional patterns
• Experience with test-driven or test-heavy development (unit/integration/regression)
• Ability to build multi-stage data processing pipelines (graph-based, batch, streaming)
• Understanding of security best practices including input validation and vulnerability remediation
• Experience with agentic AI, including LLM-based developer agents and workflow orchestration

• Collaborates effectively with cross-functional teams
• Strong attention to detail and quality focus
• Proactive in security and risk-aware development
• Python 3 proficiency with advanced features
• Test-driven development and comprehensive testing strategies
• Graph-based, batch, and streaming data pipelines

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