Senior AI Engineer - Agentic Systems

IBM

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Work type
On-site
Location
New York, NY
Posted
6 days ago

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TL;DR · Senior AI Engineer - Agentic Systems

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We are seeking a senior AI engineer to join our dynamic team in developing advanced agentic systems for an enterprise client. This role involves designing and deploying AI workflows on Azure using frameworks like LangChain and LangGraph, focusing on prompt engineering, RAG pipelines, and agent orchestration. You will work independently, interacting directly with the client to gather requirements and demonstrate technical solutions while ensuring seamless integration across various teams. Key responsibilities include building production-grade models, integrating AI capabilities into enterprise applications via APIs and microservices, and establishing robust monitoring and evaluation systems for continuous performance optimization. Ideal candidates have extensive experience in agentic AI development, LLMs, RAG architectures, and MLOps practices, along with familiarity with vector databases and Azure services like ML and AI Studio.

Skills

Azure Agentic AI Prompt Engineering RAG Pipelines LangChain LangGraph MLOps CI/CD Azure ML Azure AI Studio API Integration Event-Driven Pipelines Microservices Monitoring Evaluation Feedback Loops Security Scalability Compliance LLMs Vector Databases Enterprise APIs Workflow Platforms AI Governance Logging Guardrails Human-in-the-loop Controls

What you'll do

  • Design, build, and deploy agentic AI workflows using Azure OpenAI.
  • Develop prompt engineering strategies to enhance model performance and reliability.
  • Build Retrieval-Augmented Generation (RAG) pipelines for context-aware responses.
  • Implement agent orchestration patterns including tool calling and memory management.
  • Deploy and manage AI models on Azure ML and AI Studio services.

What we're looking for

  • 7+ years of experience in designing, developing, and deploying scalable AI applications using LLMs and RAG architectures.
  • Expertise in building and operationalizing agentic AI workflows with frameworks like LangChain and LangGraph.
  • Proficiency in developing AI agents for tool calling, memory management, multi-agent coordination, and autonomous workflow execution.
  • Experience implementing MCP integration patterns for secure, modular interoperability between AI systems and enterprise data sources.
  • Strong background in industrializing AI capabilities through reusable architecture patterns and standardized deployment frameworks.
  • Ability to develop and integrate enterprise-grade APIs, vector databases, and operational systems into AI-enabled business processes.
  • Knowledge of AI governance, security, logging, and human-in-the-loop controls for responsible AI adoption.

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