Description

Top 3 Skills: 

1. AWS Stack
2. Claude Code
3. Deep understanding of Asset Management/Financial Services

Seeking a Full Stack AI Engineer to design and deliver enterprise-grade AI applications that enhance investment processes, client reporting, and operational efficiency. This role will partner across investment teams, technology, operations, and distribution to embed AI capabilities into core workflows while adhering to strict regulatory and governance standards.

Key Responsibilities:

• Design, build, and deploy full stack AI applications leveraging Anthropic Claude and similar LLM technologies 
• Develop scalable, secure cloud-native solutions within AWS (Lambda, ECS/EKS, S3, RDS, API Gateway) 
• Build intuitive user interfaces that deliver AI-driven insights to portfolio managers, analysts, and client service teams 
• Integrate AI into investment data platforms, research workflows, and client reporting systems 
• Implement retrieval-augmented generation (RAG) solutions across structured and unstructured financial data (research, commentary, fund data, regulatory documents) 
• Partner with investment, compliance, legal, and risk teams to ensure responsible AI usage and model governance 
• Enhance and automate operational processes across middle- and back-office functions 
• Contribute to enterprise AI standards, architecture, and best practices 

Required Qualifications:

• 5+ years of full stack software engineering experience 
• Hands-on experience building and deploying LLM-powered applications (Claude strongly preferred) 
• Strong expertise in AWS and cloud-native architecture 
• Proficiency in Python and/or Node.js, with modern front-end frameworks (React preferred) 
• Experience working within asset management, wealth management, or financial services 
• Strong understanding of data engineering concepts, APIs, and distributed systems 
• Proven ability to work cross-functionally with both technical and business stakeholders 

Preferred Qualifications:

• Experience with investment data, portfolio analytics, or client reporting platforms 
• Familiarity with regulatory requirements (SEC, FINRA) and model governance frameworks 
• Experience with vector databases, embeddings, and RAG architectures 
• Exposure to MLOps and model lifecycle management 
• Experience integrating AI into enterprise workflows at scale 

Key Skills

Education

Bachelor's degree