Advanced AI Professional

4 days ago

Bengaluru, Karnataka, India beBeeArtificial Full time ₹ 1,66,40,000 - ₹ 2,51,10,000

Job Opportunity: Senior AI Developer

Position Overview

This role focuses on developing production-grade agentic AI solutions. The ideal candidate will design and develop enterprise-scale agentic AI solutions using LangGraph and related frameworks.

Key Responsibilities:
  • Develop RAG systems (chunking, retrieval strategies, evaluation) with emphasis on accuracy, latency, and reliability.
  • Architect multi-step reasoning workflows that integrate with existing enterprise systems and APIs.
  • Collaborate with cross-functional teams to translate business requirements into scalable AI solutions.
  • Ensure AI implementations meet enterprise security, compliance, and governance standards.
  • Optimize system performance and cost efficiency across multiple LLM providers.
  • Mentor junior developers and contribute to AI development best practices.
  • Partner with DevOps teams to ensure reliable production deployments.
Required Qualifications:
  • Bachelor's degree in Computer Science or a related technical field.
  • 7-10 years of software development experience with demonstrated expertise in AI/ML technologies.
  • Strong proficiency in Python with experience in asynchronous programming patterns.
  • Proven track record of implementing production LLM integrations.
  • Hands-on experience with RAG system development including vector databases, embedding models, and retrieval optimization.
  • Knowledge of enterprise software architecture patterns and API integration best practices.
  • Understanding of AI governance, security, and ethical AI principles.
  • Strong understanding of prompt engineering techniques and LLM behavior optimization.
Preferred Qualifications:
  • Experience with agent frameworks and multi-step reasoning implementations.
  • Background in machine learning, including model fine-tuning and training pipelines.
  • Previous experience developing AI agents for enterprise use cases.
  • Familiarity with cloud platforms and containerization technologies.
  • Experience with MLOps practices and CI/CD for AI systems.
  • Knowledge of enterprise data management and integration patterns.
Technical Environment:
  • Modern cloud-based infrastructure with enterprise security standards.
  • Collaborative development environment using Git, CI/CD pipelines, and agile methodologies.
  • Access to cutting-edge AI technologies and frameworks.
  • Integration with enterprise systems including CRM, ERP, and knowledge management platforms.
  • Vector databases, JSON/XML processing, API integration.

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