Principal Applied AI Engineer, Finance
Virtual Office (Massachusetts), United States
R
USD 193K-340K Senior-level Full Time
Tasks
- Architect agentic AI systems
- Build production predictive models
- Build scalable AI ML systems with APIs
- Coordinate with finance IT and product stakeholders
- Define evaluation metrics and monitoring
- Design fault tolerant observable agent systems
- Detect model drift
- Develop multi agent systems with LLMs
- Ensure SOX security compliance and auditability
- Establish MLOps best practices for deployment monitoring retraining governance
- Establish responsible AI guardrails
- Implement CI CD testing and containerization
- Implement RAG based semantic search
- Lead customer churn attrition prediction
- Lead time-series forecasting
- Mentor data specialists
- Perform feature engineering
- Set technical direction for AI/ML initiatives
- Translate predictive insights into finance recommendations
Perks/Benefits
- 401k matching
- Adoption Assistance
- Development and career growth opportunities
- Fertility treatments
- Flexible work schedules
- Open time off
- Paid Holidays
- Paid volunteer time
- Telehealth Coverage
- Well-being resources
- Work from home
Skills/Tech-stack
API Development | AWS | Bias Mitigation | CI/CD | Churn modeling | Cloud Computing | Customer churn | Customer churn modeling | Deep learning | Distributed Systems | Docker | Drift Detection | Feature Engineering | Fine Tuning | Generative AI | Guardrails | Kubernetes | Language Models | Large Language Models | MLOps | Machine Learning | Model Drift | Model Drift Detection | Model Evaluation | Model Monitoring | Orchestration Patterns | Prompt engineering | Python | RAG | Responsible AI | Semantic Search | Series forecasting | Time Series | Time Series Forecasting | Tool use | Tool-use frameworks | Vector Databases
Education
N/A
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