Job Description

Senior AI Developer - Agentic AI Solutions

Position Overview: We are seeking an experienced Senior AI Developer to join our growing agentic AI team. This role will focus on developing production-grade agentic AI solutions including ReAct agents that drive business value across multiple business units. The successful candidate will architect and implement sophisticated AI agents, RAG systems, and automation workflows that integrate seamlessly into our enterprise technology stack.

Key Responsibilities:

  • Design and develop enterprise-scale agentic AI solutions using LangGraph and related frameworks
  • Build and optimize RAG systems (chunking, retrieval strategies, evaluation) with an 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, Engineering, or 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 (OpenAI, Anthropic, Azure OpenAI, etc.)
  • 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 (LangChain/LangGraph preferred) and multi-step reasoning implementations
  • Experience with Model Context Protocol (MCP) and tool integration frameworks
  • Background in machine learning, including model fine-tuning and training pipelines
  • Previous experience developing AI agents for enterprise use cases
  • Familiarity with cloud platforms (AWS, GCP, Azure) 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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