Design, develop, and deploy autonomous AI systems as part of the Investments Technology team. Collaborate in cross-functional squads across Investments, Investments Technology, and TRP Labs to help scale responsible AI solutions across the enterprise.
This role could have the opportunity for split onsite hybrid work between our Partner's Baltimore and Washington DC locations.
Responsibilities - Design, build, test, and deploy AI agents and intelligent systems for modern cloud-based, n-tier architectures
- Partner with business stakeholders to develop agent-driven workflows that automate complex processes and generate actionable insights
- Champion engineering excellence by applying best practices in AI development, continuous integration, and code quality
- Contribute to projects on agent orchestration, prompt engineering, real-time data-driven automation, and evaluation frameworks
- Manage technical debt and drive ongoing improvements in AI platforms and infrastructure
- Proactively seek opportunities to apply AI agents for increased business value and operational efficiency
- Collaborate directly with business stakeholders to understand needs and priorities
- Make technology decisions that support current and future business objectives and fiscal responsibility
- Translate business requirements into effective technology solutions
Requirements - US Citizenship
- BS or MS in Computer Science or a related technical field (or equivalent experience), with 5+ years of professional development experience in an object-oriented language (Java, Python, or JavaScript preferred)
- Hands-on experience with cloud-native architectures (AWS, Azure), containerized microservices, and agent frameworks
- Strong analytical and problem-solving abilities
- Commitment to quality via automated testing, code reviews, and continuous delivery
- Results-driven with a passion for learning and staying current with emerging technologies
Desired Skills - Hands-on experience building LLM-powered or agent-based systems in production
- Experience with retrieval-augmented generation (RAG), vector databases, MCP servers, agent orchestration frameworks, prompt evaluation and iteration, model benchmarking, and performance testing
- Experience with Amazon Bedrock AgentCore, AWS Kiro, and OpenAI Codex
- Experience in asset management, financial markets, or quantitative research environments
- Solid understanding of financial markets, financial instruments, and financial datasets
