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Senior Full Stack AI Engineer (Agentic AI & LLM Platforms)
Job Location:
Job Location:
Minneapolis, MN - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
15 July 2026 (30+ days ago)
Posted:
Application Deadline:
12 October 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Job Title: Senior Full Stack AI Engineer (Agentic AI & LLM Platforms)
Location: Minneapolis MN
Job Type: Full-Time
Experience: 8-12 Years
Job Summary
We are seeking a Senior Full Stack AI Engineer to design build and scale enterprise-grade AI applications and shared AI platform capabilities supporting Portfolio Management and Investment Research. The ideal candidate will have extensive experience with Agentic AI LLMs Anthropic Claude RAG architectures AI orchestration and Python along with a strong understanding of financial services and cloud-native engineering. This is a hands-on engineering role responsible for developing secure reusable and governed AI solutions that accelerate enterprise AI adoption.
Required Skills
AI & Generative AI
- 8 years of software engineering or platform engineering experience
- Hands-on experience implementing:
- Agentic AI
- Large Language Models (LLMs)
- Multi-Agent Systems
- AI Automation
- AI Platform Engineering
- Strong expertise with:
- Anthropic Claude
- Claude Code
- Claude Interpreter
- Prompt Engineering
- Tool Calling
- AI Orchestration
- AI Workflows
AI Frameworks
- LangChain
- LangGraph
- LlamaIndex
- MCP (Model Context Protocol)
- RAG (Retrieval-Augmented Generation)
- Vector Databases
- Embeddings
- Semantic Search
Programming
- Python
- REST APIs
- Microservices
- Object-Oriented Programming
- Cloud-Native Development
Cloud & DevOps
- AWS Azure or GCP
- CI/CD Pipelines
- Git
- Docker
- Kubernetes
- SDLC Automation
AI Platform Engineering
- AI Platform Development
- Shared AI Services
- AI Guardrails
- AI Governance
- Responsible AI
- Model Evaluation
- Model Monitoring
- Enterprise AI Enablement
Data & Analytics
- Enterprise Data Platforms
- Structured & Unstructured Data
- Data Integration
- Analytics Platforms
- Knowledge Bases
Financial Services
- Portfolio Management
- Investment Research
- Quantitative Analytics
- Financial Services Domain
- Regulated Environments
Leadership
- Solution Design
- Technical Leadership
- Architecture Guidance
- Developer Enablement
- Cross-functional Collaboration
- Stakeholder Management
Key Responsibilities
- Design and develop enterprise-scale Agentic AI applications and AI platform capabilities
- Build multi-agent workflows using Anthropic Claude Claude Interpreter and approved AgentCore frameworks
- Develop AI solutions utilizing RAG tool calling vector databases embeddings and semantic search
- Build reusable AI components prompt libraries and enterprise AI frameworks
- Integrate AI capabilities with CI/CD pipelines SDLC tooling enterprise applications and cloud platforms
- Collaborate with Portfolio Managers Research Analysts and Quant teams to deliver AI-powered investment solutions
- Establish AI governance security controls Responsible AI practices and reusable architecture patterns
- Develop AI reference architectures documentation implementation guides and developer enablement materials
- Measure AI adoption and business impact through KPIs focused on productivity quality and engineering efficiency
- Mentor engineering teams and promote enterprise AI best practices across the organization
Preferred Qualifications
- Experience building enterprise AI platforms in financial services
- Experience with Portfolio Management Investment Research or Quantitative Analytics
- Experience integrating AI with enterprise analytics and data platforms
- Knowledge of Responsible AI model governance audit and compliance frameworks
- Experience with cloud-native architectures and distributed systems
