Junior AI Engineer

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.

• 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.

Education

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

Experience and Skills

• Good Python 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.