Primary Skills
- Intent Model Testing - K-means/K-Folds, Accuracy/Precision, F-scores, Overall Accuracy, Inten Model Balancing - Overvfit vs Underfit, Negative Corpus
Job requirements
Technology Stack:
• Strong hands-on experience with AWS infrastructure (Bedrock, Bedrock Agents, Lambda, ECS/EKS, Step Functions, S3, IAM)
• Proficiency in Python, LangChain/LangGraph, agentic frameworks, and prompt engineering
• Experience with RAG pipelines, embedding models, vector stores, and evaluation frameworks
Domain Expertise:
• Proven experience delivering AI/GenAI use cases for financial services
Key Role Expectations:
• Partner with the AI Architect to convert the architecture into an actionable execution plan and sprint backlog
• Lead the AI engineering pod day-to-day; drive technical delivery, code quality, and engineering standards
• Own implementation of core AI components — agents, orchestration, RAG, model integration
• Conduct design reviews, pair with engineers on complex problems, and unblock the team
• Ensure adherence to security, observability, cost, and performance guardrails
• Coordinate across AI Engineers, Platform Engineers, and SREs for integrated delivery