Dutech’s Job

We are looking for a highly skilled Senior AI/ML Engineer with deep expertise in Generative AI, Large Language Models (LLMs), and autonomous agent frameworks. The ideal candidate will have hands-on experience building and deploying production-grade AI agents, implementing RAG architectures, and working with modern AI frameworks such as LangChain, LangGraph, CrewAI, or AutoGPT.

This role involves designing scalable, secure, and efficient AI systems for enterprise applications.

Key Responsibilities:

• Design, build, and deploy production-grade autonomous AI agents
• Develop and implement RAG (Retrieval-Augmented Generation) architectures using vector databases
• Work with frameworks such as LangChain, LangGraph, CrewAI, and AutoGPT
• Integrate and optimize LLMs via APIs (OpenAI, Hugging Face, Azure AI)
• Implement context engineering strategies to enhance LLM performance
• Build and manage multi-agent workflows and orchestration systems
• Apply AI governance, model lifecycle management, and evaluation frameworks
• Implement AI guardrails, content filtering, and safety controls
• Ensure compliance with data privacy standards (PII/PHI handling)
• Optimize LLM performance, cost, and token usage
• Collaborate with cross-functional teams to design scalable AI solutions

Required Qualifications:

• 4+ years of experience in AI/ML Engineering or Advanced Data Science
• Proven experience building and deploying autonomous AI agents in production
• Strong hands-on experience with LangChain, LangGraph, CrewAI, or AutoGPT
• Experience implementing RAG architectures with vector databases
• Proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI)
• Experience integrating LLMs via APIs
• Strong understanding of AI governance, model lifecycle, and evaluation
• Experience with Model Context Protocol (MCP) and secure data access for LLMs
• Knowledge of AI safety, guardrails, and content moderation
• Understanding of data privacy and sensitive data handling

Preferred Qualifications:

• Experience building multi-agent or agentic workflows
• Experience optimizing LLM cost, latency, and token usage
• Familiarity with enterprise AI deployment and scalability patterns