AI Agent Developer

Key Responsibilities - Solution Development: Design, architect, and implement AI Agent systems that automate or augment complex financial workflows, including trade support, market research synthesis, client communications, and data analysis. - LLM Integration & Orchestration: Build and maintain multi-step agent pipelines leveraging frameworks such as Dify, or equivalent orchestration platforms. Integrate with Bloomberg API, internal data infrastructure, and third-party data providers to deliver domain-specific AI capabilities. - Prompt Engineering: Develop, evaluate, and optimize structured prompts and agent instructions to ensure accuracy, consistency, and compliance-readiness in LLM-generated outputs across financial contexts. - Rapid Prototyping & Validation: Translate business requirements into functional prototypes on compressed timelines. Validate solution feasibility through iterative testing with end users and subject matter experts. - Stakeholder Engagement: Partner with traders, portfolio managers, distribution professionals, and compliance officers to identify automation opportunities, gather requirements, and ensure delivered solutions meet institutional quality standards. - Production Transition: Prepare comprehensive technical documentation, architecture diagrams, and operational runbooks to support handoff of validated solutions to the platform engineering team for production deployment and ongoing maintenance. - Technology Evaluation: Monitor and assess emerging AI capabilities, tooling, and best practices. Provide structured recommendations to senior leadership on technology adoption and strategic direction. Qualifications - Bachelor's degree or above in Computer Science, Engineering, Mathematics, or a related quantitative discipline. - Strong proficiency in Python; working knowledge of JavaScript/TypeScript is advantageous. - Demonstrated experience with large language models, AI agent frameworks (AutoGen, CrewAI, Dify, or comparable), and prompt engineering methodologies. - High proficiency with AI-assisted development environments including GitHub Copilot, Cursor, Claude, and GPT-based tooling. - Excellent English communication skills — both written and verbal — with the ability to produce clear technical documentation and precise model instructions. - Strong analytical and problem-solving capabilities; ability to decompose complex, ambiguous business problems into structured, deliverable engineering tasks. - Self-directed work style with the ability to manage multiple concurrent initiatives and deliver under time constraints.

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