Agentic AI Engineer

Job Title: Agentic AI Engineer

Location: Boston, MA

Job Summary

We are seeking an experiencedAgentic AI Engineer to design and develop next-generation AI applications using modern agent frameworks and Large Language Models (LLMs). The ideal candidate will have hands-on experience building autonomous and multi-agent systems usingLangChain, LangGraph, DeepAgents, and Skill Agents, along with expertise in Python, RAG, and cloud-based AI platforms.

Key Responsibilities

• Design, develop, and deploy Agentic AI solutions for enterprise applications.
• Build autonomous and multi-agent workflows usingLangChain, LangGraph, DeepAgents, and Skill Agents.
• Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases.
• Integrate LLMs such as OpenAI GPT, Claude, Gemini, or Llama with enterprise applications.
• Create AI agents capable of tool calling, function calling, and workflow orchestration.
• Develop REST APIs and microservices to support AI applications.
• Optimize prompts, agent memory, reasoning, and response quality.
• Collaborate with product managers, data scientists, and software engineers to deliver scalable AI solutions.
• Deploy AI applications on AWS, Azure, or GCP using Docker and Kubernetes.
• Monitor and improve AI performance, reliability, and security.

Required Skills

• 5+ years of software development experience.
• 2+ years of experience building LLM and Agentic AI applications.
• Strong proficiency inPython.
• Hands-on experience with:
  • LangChain
  • LangGraph
  • DeepAgents
  • Skill Agents
• Experience with Retrieval-Augmented Generation (RAG).
• Knowledge of vector databases such as Pinecone, ChromaDB, Weaviate, FAISS, or Milvus.
• Experience with OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or Llama models.
• Strong understanding of Prompt Engineering and AI agent architecture.
• Experience building REST APIs using FastAPI or similar frameworks.
• Familiarity with Git, Docker, and Kubernetes.
• Experience with cloud platforms (AWS, Azure, or GCP).

Preferred Qualifications

• Experience with CrewAI, AutoGen, or Semantic Kernel.
• Knowledge of Model Context Protocol (MCP).
• Experience with AI evaluation frameworks such as LangSmith, DeepEval, or Ragas.
• Understanding of MLOps and AI deployment best practices.
• Experience with CI/CD pipelines and enterprise software development.

Education

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field