AI Solutions Engineer - Vice President

TL;DR

AI Solutions Engineer (Vice President) (AI/Data Engineering): Architect and deliver AI-powered data engineering solutions — LLM agents, RAG pipelines, and multi-agent workflows for pipeline generation, schema mapping, data quality, and migration — using tool-calling, stateful memory, and multi-agent coordination, integrated with WM Lakehouse platform. Focus on defining AI evaluation standards, owning AI delivery lifecycle, enforcing responsible AI practices, and partnering with data architects for governance compliance.

Location: Dallas, Texas, United States (office)

Company

Leading global investment banking, securities and investment management firm headquartered in New York with offices around the world.

What you will do

• Architect and deliver AI-powered solutions including LLM agents, RAG pipelines, and multi-agent workflows integrated with S3, Databricks, Snowflake, Glue, Athena, MWAA
• Define and maintain AI evaluation standards: offline benchmarks, prompt versioning, regression testing, production observability
• Own AI delivery lifecycle: CI/CD for models and prompts, automated testing, release management
• Enforce responsible AI: output guardrails, prompt injection defenses, PII handling on sensitive financial data
• Partner with data architects to ensure compliance with governance standards (GDPR, CCPA, SOC2) and leverage Lakehouse infrastructure
• Establish AI integration patterns (Model Context Protocol, AWS Bedrock) and mentor associate/analyst engineers

Requirements

• 7+ years software engineering, 3+ years production AI/ML systems, LLM/agentic architectures
• Proficiency in Java, Python, SQL; hands-on with LLM APIs (OpenAI, Anthropic), agentic frameworks (LangChain, LangGraph)
• Experience designing agentic architectures: tool use, multi-agent orchestration, memory, state management
• Working knowledge of cloud data platforms: S3, Glue, Snowflake, Athena, MWAA/Airflow, Lakehouse, ETL/ELT
• Experience building AI evaluation pipelines (LangSmith, RAGAS, PromptFoo)
• Excellent communication; ability to lead cross-functional initiatives

Nice to have

• Experience with tool-integration patterns for LLM agents (Model Context Protocol)
• Data governance tooling: metadata, lineage, quality frameworks, AWS Lake Formation
• Familiarity with Apache Iceberg, Spark, Databricks, Snowflake
• Event-driven architecture, streaming pipelines, real-time inference
• Infrastructure as code (AWS CDK, Terraform, CloudFormation)
• Background in financial services or regulated data environments

Culture & Benefits

• Commitment to diversity, inclusion, professional growth through training, networks, benefits, wellness programs
• Best-in-class benefits including health insurance, personal finance offerings, mindfulness programs
• Reasonable accommodations for candidates with special needs or disabilities
• Equal opportunity employer