AI Engineer with Python

AI Engineer

Locations: Plano, TX | Columbus, OH | Wilmington, DE

Job Summary

We are seeking an experienced AI Engineer to design, develop, and deploy AI-powered applications using modern machine learning and generative AI technologies. The ideal candidate has strong programming skills in Python and Java, along with hands-on experience building Agentic AI solutions using LLMs, orchestration frameworks, and cloud-native architectures.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 5+ years of software engineering experience with a focus on AI/ML applications.
• Strong proficiency in Python and Java.
• Experience designing and implementing Agentic AI systems using Large Language Models (LLMs).
• Hands-on experience with AI orchestration frameworks such as LangGraph, LangChain, AutoGen, CrewAI, or similar.
• Experience integrating AI applications with REST APIs, databases, and enterprise systems.
• Strong understanding of prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, vector databases, and AI workflows.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Familiarity with containerization and orchestration technologies including Docker and Kubernetes.
• Experience with Git, CI/CD pipelines, and Agile development methodologies.
• Strong analytical, debugging, and problem-solving skills.

Preferred Qualifications

• Experience working with OpenAI, Anthropic, Google Gemini, or open-source LLMs.
• Knowledge of AI observability, evaluation, guardrails, and model monitoring.
• Experience with vector databases such as Pinecone, Chroma, FAISS, or Milvus.
• Familiarity with MLOps practices and model deployment pipelines.
• Experience building conversational AI, AI assistants, or autonomous agents.

Key Responsibilities

• Design and develop scalable AI applications using Python and Java.
• Build and deploy Agentic AI solutions capable of planning, reasoning, and executing multi-step workflows.
• Develop LLM-powered applications using prompt engineering, RAG, and vector search techniques.
• Integrate AI services with enterprise applications, APIs, and data platforms.
• Optimize AI model performance, latency, and cost.
• Collaborate with product managers, data scientists, architects, and software engineers to deliver AI-driven solutions.
• Implement testing, monitoring, security, and governance for AI applications.
• Stay current with advancements in Generative AI, Agentic AI, and emerging AI technologies.