Associate Software Engineer (AI Engineering)

TL;DR

Associate Software Engineer (AI Engineering): Designing and building AI-powered tools for investment analysis and portfolio management with an accent on production-grade LLM applications. Focus on implementing RAG systems, agentic AI architectures, and scalable backend services to transform financial workflows.

Location: Dallas, TX, United States (Onsite)

Company

A global investment banking and asset management firm overseeing more than $2 trillion in assets for diverse institutional and individual clients.

What you will do

• Build and maintain AI-powered applications that automate and enhance investment workflows.
• Design and develop APIs, data pipelines, and backend services to integrate AI models into existing platforms.
• Implement retrieval-augmented generation (RAG) systems, prompt engineering frameworks, and agentic AI architectures.
• Collaborate with investment professionals, data scientists, and product stakeholders to translate business needs into technical solutions.
• Ensure the reliability, scalability, and security of AI-driven applications in a production environment.
• Evaluate emerging AI tools and frameworks to determine practical applications for the business.

Requirements

• 2+ years of software engineering experience.
• Proficiency in Python and at least one additional language such as Java or TypeScript.
• Experience building and deploying applications leveraging large language models (LLMs) or generative AI.
• Understanding of commercial and open-source LLMs including OpenAI, Gemini, Llama, and Claude.
• Experience with retrieval-augmented generation (RAG) and vector stores.
• Familiarity with RESTful APIs, cloud services, and modern software development practices.

Nice to have

• Experience with AI orchestration frameworks like LangChain or LlamaIndex.
• Familiarity with Graph RAG and knowledge graphs for complex data relationships.
• Experience with prompt engineering and optimization techniques.
• Exposure to cloud platforms such as AWS, GCP, or Azure.
• Experience with containerization tools like Docker and Kubernetes.
• Background in financial services or fintech.