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