AI Solutions Engineer

• Build and deploy end‑to‑end GenAI solutions using RAG, agent frameworks, and MCP servers, linking LLMs with internal systems through APIs from major AI providers.
• Work closely with investment and business teams to surface impactful use cases, convert requirements into technical workflows, and deliver training, prompts, and clear documentation.
• Develop structured evaluation methods to compare external AI tools, agents, and models across investment and financial datasets, ensuring strong performance and reliability.
• Stand up secure, scalable AI/LLM environments on cloud platforms (AWS, Azure, GCP, Snowflake, Databricks) to address business needs quickly.
• Test and implement new AI technologies
  

• 5+ years in applied AI, solution engineering, or technical product work.
• Degree in Computer Science, Engineering, Applied Mathematics, or related field.
• Strong grasp of the modern AI ecosystem: transformers, agent workflows, context/prompt design, model evaluations, and LLM orchestration.
• Hands‑on experience adapting and integrating GenAI tools (e.g., ChatGPT, Claude, Gemini, Perplexity, DeepSeek, GitHub Copilot, Cursor) into real business pipelines.
• Skilled in Python, SQL, and GitHub, with working knowledge of major cloud/data platforms (AWS, Azure, GCP, Snowflake, Databricks).
• Experience in financial services, hedge funds, asset management, or fintech, is beneficial.
• Professional fluency in English; Mandarin is advantageous.

Desired Traits

• Self‑driven, proactive, and comfortable working independently.
• Detail‑oriented, results‑focused, and reliable under pressure.
• Collaborative team contributor with strong work ethic and maturity.
• Able to translate complex technical concepts into simple explanations for non‑technical audiences.