Asset & Wealth Management - AI Solutions Engineer - Associate - Dallas

Responsibilities

• Build and maintain AI-powered data engineering tools — LLM agents for pipeline generation, schema mapping, data quality analysis, and migration — integrated with the WM data platform (S3, Databricks, Snowflake, Glue, Athena, MWAA)
• Build and iterate on evaluation frameworks (LangSmith, RAGAS, PromptFoo) to measure and improve AI output quality across data engineering workloads
• Write well-tested, production-quality code with comprehensive unit and integration tests for AI components
• Implement responsible AI practices in every system: output guardrails, prompt injection defenses, PII handling, and audit logging — especially critical when operating on sensitive financial data
• Implement and maintain backend services and APIs that expose AI-driven data tooling platform engineers and internal stakeholders
• Collaborate with senior engineers, data architects, and business stakeholders to scope requirements, prototype solutions, and ship iteratively
• Actively seek feedback, grow technical breadth across AI and data engineering, and contribute to team knowledge-sharing

Qualifications

• 3+ years of software engineering experience, including hands-on work with machine learning models or AI application development
• Proficiency in Java, Python, and SQL; hands-on experience with LLM APIs or agentic frameworks (OpenAI, Anthropic, LangChain, or similar)
• Familiarity with agentic patterns: tool use, multi-step reasoning, and structured output generation
• Understanding data engineering concepts — ETL/ELT pipelines, data warehousing, data lake architectures, or cloud data services (S3, Glue, Databricks, Snowflake)
• Awareness of responsible AI concerns — prompt injection, hallucination risk, output guardrails, data leakage
• Strong analytical and problem-solving skills; effective written and verbal communication