Junior AI Engineer

Ex; United States; On-site; USD 90,000 - 130,000; Full time

Job summary

Ex in the United States is seeking an AI Engineer-AI Solutions Architect to prototype and own small-to-medium parts of AI solutions. You will build and test AI agents, write Python code for AI workflows, and collaborate with clinical experts to deliver practical healthcare AI applications.

You will work with teams to turn business needs into working prototypes, maintain clean documentation, and continue learning new AI tools and methods in a hands-on environment.

Qualifications

• Bachelor's degree in a technical field such as engineering, CS, data science or AI.
• Basic understanding of ML and how large language models work.
• Hands-on AI project experience with code or a demo.
• Familiarity with at least one LLM tool or framework (LangChain, LlamaIndex, OpenAI/Azure APIs).
• Comfort using Git and Linux environment.
• Clear written and spoken communication.

Responsibilities

• Build and test AI applications that use LLMs, prompt design, and retrieval-based methods.
• Write clean, well-documented Python code for AI workflows and API connections.
• Help build AI agents and multi-step workflows that use tools and decision paths.
• Test model outputs for accuracy, consistency, and clarity; report issues clearly.
• Prepare and work with healthcare data such as policies, claims, and clinical content.
• Handle sensitive health data, following privacy rules.
• Collaborate with product owners, clinical experts, and senior engineers to deliver solutions.
• Document experiments, designs, and results for reuse; share progress with your manager.
• Keep learning about new AI tools and methods.

Skills

Machine Learning basics

LLM concepts

Python programming

Git

Communication

Education

Bachelor's degree in engineering/computer science/data science/AI

Tools

LangChain

LlamaIndex

OpenAI APIs

Azure OpenAI

Linux

Job description

• Job Role AI Engineer-AI Solutions Architect
• Experience (In Years) 0-3
• Job Location United States

Job Description

You will build and test AI agents and workflows that support human experts rather than replace their judgment. This is a hands-on role. You will prototype quickly, learn from experienced colleagues, and grow into owning larger parts of our solutions.

Responsibilities

Build and test AI applications that use large language models (LLMs), prompt design, and retrieval-based approaches.

Write clean, well-documented Python code for AI workflows, including connections to other systems through APIs.

Help build AI agents and multi-step workflows that use tools and follow decision paths.

Test model outputs for accuracy, consistency, and clarity, and report issues with clear notes.

Prepare and work with healthcare data such as policies, claims, and clinical content for AI use.

Handle sensitive health data (personal and health information) carefully, following company and client privacy rules.

Work with product owners, clinical experts, and senior engineers to turn business needs into working solutions.

Document experiments, designs, and results so others can reuse them.

Share progress and blockers with your manager on a regular basis.

Keep learning about new AI tools and methods.

Qualifications

Education

Bachelor’s degree in engineering, computer science, data science, AI, or a related technical field.

Experience and Skills

Basic understanding of machine learning and how large language models work.

Hands-on AI project experience (work, internship, academic, or personal) that you can show through code or a demo.

Familiarity with at least one LLM tool or framework, such as LangChain, LlamaIndex, or the OpenAI or Azure OpenAI APIs.

Comfort using Git and working in a Linux environment.

Clear written and spoken communication.

Preferred Qualifications

Experience with AI agent frameworks and workflow tools.

Experience with a cloud platform (Azure, AWS, or Google Cloud).

Basic SQL and data handling skills.

Exposure to healthcare data or U.S. health plan operations (preferred, not required).

Familiarity with healthcare data standards such as FHIR.

Internship or project work building or testing LLM-based applications.

What Success Looks Like

You deliver working prototypes within your first few months.

Your code is reliable and well documented.

You can explain your results to non-technical teammates.

You take on larger pieces of work as you grow.