Exp : 5 - 10 Years
Mode of work : Hybrid Model
Work Location : Bangalore
Role Overview :
- 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.
Tavant Technologies - Agentic AI Engineer • Bangalore
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