AI Agent Software Engineer

5+ years of professional Python development experience, preferably in a sell-side bank, hedge fund, or proprietary trading environment
Strong background in traditional finance with hands-on experience implementing financial workflows and processes
Proven experience building applications and systems in financial services environments
Solid understanding of financial products, services, and the level of complexity required for financial coding
Strong problem-solving skills and ability to translate complex financial requirements into technical solutions
Ambitious mindset with openness to AI and ability to see the transformative potential of intelligent automation
Experience with cloud infrastructure (AWS preferred) and modern development practices
Strong communication skills and ability to collaborate effectively with cross-functional teams
No AI experience required – we’ll teach you our framework and approach

Design, implement, and maintain autonomous AI agents using Python and AWS that serve clients and automate complex financial workflows
Build and scale robust data pipelines leveraging Pandas, SQLAlchemy, and PostgreSQL to power intelligent agent decision-making
Deploy and manage high-performance workloads using AWS Lambda, S3, EC2, and related cloud services
Collaborate closely with product and trading teams to integrate sophisticated financial data models and business logic into agent behavior
Construct and maintain internal knowledge graphs that enable agents to understand complex financial relationships and processes
Monitor agent performance, reliability, and latency in production environments and continuously iterate for improvement
Build agents across key areas including data onboarding, project management, client experience and operations tasks, and client acquisition workflows
Support trading operations in international securities through intelligent automation and workflow optimization
Translate your traditional finance experience into AI-powered solutions that understand the complexity of financial services operations
Drive technical decisions for agent architecture that scales with our growing client base and expanding service offerings

Experience with LLM-based applications or AI/ML frameworks
Knowledge of financial modeling and quantitative analysis
Exposure to knowledge graph frameworks, ontologies, or graph databases
Experience automating complex operational tasks using agents or advanced scripting
Familiarity with asynchronous programming, concurrent systems, or distributed task queues
Working knowledge of financial data, order lifecycles, or middle/back office operations
Experience with financial regulatory requirements and compliance