AI Software Engineer - Fixed Income Technology

Job summary

We are seeking a talented Mid-Level AI Software Engineer to join our growing Fixed Income Technology team. In this role, you will design, develop, and deploy AI-powered capabilities that drive real business impact. You will work closely with business stakeholders, engineering, and data engineering teams to build scalable, production-grade AI systems.

Benefits

Qualifications

• Bachelor's or master’s degree in computer science, Machine Learning, or a related quantitative field
• 4+ years of professional software development experience, with 2+ years focused on building and deploying AI solutions in production environments
• Experience in Fixed Income Markets or a related financial sector
• Strong proficiency in Python and AI/agentic frameworks, including LangChain and LangGraph
• Proven ability to design, build, and architect production-grade agentic workflows and enterprise AI systems using LLMs
• Proficiency in SQL and Snowflake; comfort working with APIs and data pipelines
• Hands-on experience with cloud platforms (AWS or Azure), including native AI services such as Azure AI Foundry, AWS Bedrock, and MCP
• Solid software engineering fundamentals — version control (Git), CI/CD, testing, and containerization (Docker)
• Strong problem-solving
• into scalable technical solutions
• Experience with prompt engineering and retrieval-augmented generation (RAG)
• Preferred

Responsibilities

• In this role, you will design, develop, and deploy AI-powered capabilities that drive real business impact.
• You will work closely with business stakeholders, engineering, and data engineering teams to build scalable, production-grade AI systems.
• Evaluate, design and architect AI Tooling for production use cases within the Fixed Income business solving real-world business problems
• Build and maintain end-to-end AI powered solutions covering data ingestion, feature engineering, model training, evaluation, and deployment.
• Integrate large language models (LLMs) and foundation models into product features, including prompt engineering, fine-tuning, and RAG architecture.
• Partner with the FI business users to design and build agentic workflows
• Collaborate with data engineers to ensure high-quality, well-structured training datasets and feature stores.
• Write clean, well-tested, and well-documented code following engineering best practices.
• Participate in code reviews, design discussions, and knowledge-sharing sessions with the broader engineering team.
• Stay current with advances in AI/ML research and evaluate emerging

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