AI Engineer with Python

Job Title: 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.