Snowflake AI Engineer with Asset Management Exp - Our W2 Only (NO C2C)

Location: Atlanta, GA

Our W2 Only (NO C2C / C2H)

Snowflake AI Engineer with Asset Management Exp Required.

We need 10+ Years of experience Required.

NO STUDENT VISAS PLEASE (NO OPT / CPT)

About the Role

Our client, a large, leading U.S. asset manager, is seeking an AI Engineer to join a growing team building next-generation AI capabilities across the investment management platform. This is a high-visibility opportunity to design, build, and scale AI-powered applications and data pipelines that directly support portfolio management, research, and operational decision-making. The ideal candidate combines strong software/ML engineering skills with hands-on experience in Snowflake and modern cloud data architecture.

What You''''''''ll Do

• Design, build, and deploy AI/ML pipelines and applications (including LLM-based tools, retrieval-augmented generation systems, and predictive models) that support investment and business use cases
• Architect and optimize data pipelines in Snowflake, including ingestion, transformation, and modeling of large-scale structured and unstructured datasets
• Partner with data scientists and quants to productionize models — from prototype to scalable, monitored, production-grade systems
• Build and maintain integrations between Snowflake and AI/ML tooling (e.g., Snowpark, Cortex, vector search, external model APIs)
• Implement robust MLOps practices: CI/CD for ML, model versioning, monitoring, and retraining workflows
• Collaborate with data governance, security, and compliance teams to ensure AI systems meet the firm''''''''s standards for data privacy, auditability, and risk management
• Evaluate and prototype emerging AI technologies (LLMs, agentic frameworks, vector databases) and assess their applicability to the firm''''''''s investment and operational workflows
• Write clean, well-tested, maintainable code and contribute to engineering best practices across the team

What We''''''''re Looking For

Required:

• Prior professional experience working at an asset manager, investment manager, hedge fund, or closely related buy-side investment firm — this is a firm requirement, not a nice-to-have
• Working knowledge of investment management concepts and data: securities master/reference data, portfolio holdings and performance, market data, benchmarks, and/or investment research workflows
• Understanding of the regulatory, compliance, and data governance considerations specific to investment management (e.g., MNPI/information barriers, data lineage, model risk management)
• 4+ years of experience in software engineering, data engineering, or ML engineering roles
• Hands-on production experience with Snowflake (data modeling, performance tuning, Snowpark, security/role-based access)
• Strong programming skills in Python (SQL fluency required as well)
• Experience building and deploying machine learning models or AI applications in production environments
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform) and modern data architecture patterns
• Experience with version control, CI/CD, and software engineering best practices
• Strong communication skills and ability to work cross-functionally with investment professionals (portfolio managers, analysts, traders) as well as technical stakeholders

Preferred:

• Experience with LLM application development (prompt engineering, RAG architectures, agentic workflows, vector databases such as Pinecone/Weaviate/Snowflake Cortex Search)
• Experience with orchestration tools (Airflow, dbt, Dagster)
• Background in financial services, asset management, or another regulated industry
• Exposure to MLOps tooling (MLflow, Kubeflow, SageMaker, etc.)
• Bachelor''''''''s or advanced degree in Computer Science, Engineering, Data Science, or related field