Data Scientist/AI-ML Engineer

**Job Description** - Design and develop end-to-end agentic AI workflows and RAG pipelines using LangChain and LangFlow - Build and maintain production-grade Python services and microservices exposing AI capabilities through REST APIs and event-driven interfaces - Develop reusable Python libraries and utilities that accelerate AI pipeline development, data transformations, and integration workflows - Build GenAI-powered financial document parsing solutions for extracting and analyzing accounting statements for audit and business insights - Develop data orchestration pipelines with master data propagation, quality validation, and freshness checks across downstream systems - Design conversational AI chatbots and self-service interfaces for internal users to query enterprise data, reports, and business processes - Create embeddable UI components that integrate AI capabilities into existing enterprise platforms - Implement enterprise integrations including SSO, Slack workflows, and LLM provider APIs across AWS Bedrock and related AWS AI services - Containerize and deploy Python-based AI services on Kubernetes with high availability and operational observability - Build, train, and run comparative analysis of ML models to select optimal approaches for business problems - Implement MLOps pipelines using Airflow and maintain model observability using Grafana, Arize, or similar tools - Write clean, well-documented, and testable Python code following unit testing, CI/CD, and code review standards - Provide ongoing support and maintenance for deployed AI models, pipelines, and services in production - Stay current with emerging trends in Generative AI and agentic frameworks to continuously enhance solution quality