Junior AI Engineer

EXL•United States,

About The Position

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.

Requirements

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

Nice To Haves

  • 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.

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.
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