AI Agent Development Engineer (Autonomous Customer Systems)

Quick Facts

• Role: AI Agent Development Engineer (Autonomous Customer Systems)
• Focus: LLM-powered autonomous agents that reason, plan, use tools, and execute multi-step actions
• Scope: Architecture, tool/API integration, memory/context, prompt optimization, testing/evals & safety, production deployment and scaling

Description

You will design, build, and deploy autonomous AI agents that leverage Large Language Models (LLMs) to reason, plan, use tools, and complete multi-step actions to achieve specific goals. The role emphasizes end-to-end agent behavior—handling non-determinism with continuous testing, monitoring, and adaptation—rather than only optimizing models in isolation. You’ll translate real business workflows into reliable, safe agentic automation.

Role Description

You will build the next generation of intelligent automation and help deliver goal-driven systems that improve how customer support operations run.

Responsibilities

• Design & Architecture: Create foundational AI agent architecture, including reasoning engines and decision-making workflows.
• Agent Development: Build autonomous agents using frameworks such as LangChain, LangGraph, AutoGen, or CrewAI.
• Tool Integration & APIs: Connect agents to external tools, databases, APIs, and business systems for seamless action-taking.
• Memory & Context: Implement short- and long-term memory (e.g., vector databases and RAG) to maintain context across complex tasks.
• Prompt Engineering: Author domain-specific prompts and chain-of-thought workflows to guide agent reasoning and optimize performance.
• Testing & Reliability: Implement human-in-the-loop controls, evaluation frameworks (“evals”), and safety guardrails for ethical, reliable behavior in production.
• Deployment & Scaling: Deploy and scale agents in production using Docker, Kubernetes, and cloud platforms (AWS/Azure/GCP).

Requirements

• BS in Computer Science/Computer Engineering (or related) or equivalent professional work experience
• 7+ years of professional software development experience
• 2+ years of professional experience developing backend systems or AI/ML applications
• Strong proficiency in TypeScript
• Experience with at least one major AI agent framework: LangChain, AutoGen, LangGraph, or Semantic Kernel
• Deep understanding of LLMs (capabilities, limitations, practical application)
• Practical experience with Retrieval-Augmented Generation (RAG) and fine-tuning techniques
• Experience with vector databases (Pinecone, Milvus, Qdrant) and SQL/NoSQL databases
• Proficiency with AWS/Azure/GCP and containerization for deployment (Docker, Kubernetes)

Benefits

• Build reliable, safe autonomous AI systems for real customer support use cases
• Work in an environment focused on end-to-end goal-driven agent behavior and continuous improvement
• Collaborate across teams to convert complex business problems into agent-based solutions