Agentic AI Engineer

Work Mode : Hybrid, 3days WFO from client location

Interview process : 2 Technical TAVANT (One is face to face from any TAVANT location) + client round

Location : Bangalore , Booking office

Experience : 6 - 12years

Mandatory skills : Python coding, Agentic AI , AWS, RAG, Langchain and Langflow

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

Roles & Responsibilities

• Experience working with GenAI solutions using LLMs
• Proficiency with LangChain and LangFlow frameworks for building and testing Generative AI workflows and agentic pipelines
• Proficiency in Python for AI/ML development, microservice development, and automation
• Proficiency in core Python libraries such as pandas and NumPy
• Experience with RAG pipeline design, LLM integration, and vector store management
• Experience with ML model building and comparative analysis
• Exposure to AI/ML frameworks such as TensorFlow, PyTorch, scikit-learn, etc.
• Experience with Hugging Face
• Understanding of NLP techniques such as text summarization, sentiment analysis, and Named Entity Recognition (NER)
• Hands-on experience building and deploying REST APIs and event-driven Python services
• Experience with ML Ops tooling, particularly Airflow
• Experience with observability tools such as Grafana, Arize, or similar
• Knowledge of enterprise AI infrastructure and best practices on AWS
• Familiarity with Kubernetes for containerized workload deployment and management
• Experience with enterprise integrations including SSO, Slack workflows, and embeddable UI development
• Experience with financial document parsing, data orchestration, and conversational AI interface development
• Experience designing, developing, deploying, and maintaining software in production environments
• Experience working in a Scrum/Agile environment
• A CS, Engineering, or related university degree is a must-have
• Excellent written and verbal communication skills in English, with the ability to collaborate cross-functionally and present solutions to client stakeholders

Skills To Be Evaluated On

AWS,LangChain,Agentic AI,Python,Grafana,RestAPI,Pandas,Numpy