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. 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 * 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.