AI Engineer

Insight Global; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Insight Global is seeking a Data Scientist or AI Engineer to design and deploy AI solutions using LLMs, agent frameworks, and cloud platforms within a healthcare analytics environment. You will build AI agents, integrate with APIs and databases, deploy ML solutions to cloud or on-prem, and collaborate with engineering and business teams to deliver production-ready AI architecture.

Experience in Python, MLOps, and modern agent frameworks such as LangChain, LangGraph, OpenAI Agents is highly

Job description

Summary: We're seeking a Data Scientist or AI Engineer with experience building and deploying AI solutions using LLMs, Agentic AI frameworks, and cloud platforms.

This team is focused on developing AI agents that automate analytical workflows and generate business insights within a large-scale healthcare analytics environment.

Candidates with professional, academic, research, internship, Master's, or PhD experience developing GenAI, Agentic AI, MLOps, or cloud-based AI solutions are encouraged to apply.

Strong hands-on Python experience, experience deploying AI or ML solutions, and familiarity with modern agent frameworks such as LangGraph, LangChain, AutoGen, CrewAI, OpenAI Agents, or similar technologies are highly valued.

What You'll Be Doing

• Design and build AI agents using modern LLM frameworks


• Develop agentic workflows that automate complex business processes


• Integrate AI systems with APIs, tools, databases, and external services


• Deploy machine learning and AI solutions to cloud and on-prem environments


• Build orchestration pipelines including validation, routing, and guardrails


• Collaborate with engineering and business teams to define and deliver AI solutions


• Contribute to production-ready AI architecture and deployment practices

Required Qualifications

• 3+ years of Python development in cloud-based environments


• 2+ years building and deploying machine learning or AI solutions


• Experience with agent orchestration frameworks such as LangGraph, LangChain, OpenAI Agents, or ADK


• Experience building AI agents using local or cloud-hosted LLMs


• Experience with API integrations, tool calling, workflow orchestration, and state management


• Experience with Git and modern software development practices


• Experience with Google Cloud Platform (GCP)

Preferred Qualifications

• Experience with Vertex AI, Kubernetes, or containerized deployments


• Experience supporting production LLM applications


• Experience with AI evaluation, monitoring, or LLMOps practices


• Master's degree or PhD in Computer Science, Data Science, AI, Machine Learning, or a related field