Junior AI Engineer
Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Oct 14, 2026. EXL scores B on the Alion truth index.
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.