AI Engineer- Python - AWS - USC/GC Only

Key responsibilities: Build and deploy the platform Configure bounded AI agents that break down approved tasks, call approved tools and data services, draft outputs, create work queues and escalate to people. Build retrieval and source-citation features that show the exact record elements, dates and excerpts behind each AI output, including uncertainty and missing information. Build ingestion pipelines for structured, semi-structured and unstructured healthcare data (clinical notes, reports, policies, requirements documents), with data lineage, quality checks and retention controls. Work with business/clinical users to gather feedback and iterate rapidly. Troubleshoot issues across configuration, APIs, data, AI behavior and workflow orchestration. Maintain and prioritize the configuration/FDE backlog. Apply clinical and operational NLP to extract diagnoses, results, orders, appointments, consult details and referral prerequisites. Build risk and criticality classifiers with thresholds the client can tune by specialty, facility and policy. Build role-based review queues and case views for clinicians, nurses, referral coordinators and program managers. Work forward-deployed with client users Run discovery sessions with client subject matter experts at least every two weeks and turn what you learn into user stories and working features. Model referral pathways, prerequisites and status transitions with referral coordination teams. Support service blueprinting by synthesizing stakeholder interviews and documents into blueprints, data maps and requirements. Deliver demos at sprint reviews and adjust quickly based on user feedback. Ship in a regulated environment Deliver code in SAFe sprints (26 per year) with weekly release windows on a cloud platform (AWS).Write automated unit, integration and regression tests and use CI/CD pipelines. Track requirements, code, tests and risks in Atlassian tools (Jira, Confluence) so every requirement traces to tests. Measure output quality, reviewer agreement, false positives and negatives, and drift, and help write model cards and evaluation reports. Provide Tier III production support, and write technical design and operating documentation for transition.

Required qualifications: Bachelor's degree in computer science, engineering or a related field, or equivalent experience.5+ years of software engineering experience, including 3+ years building and shipping LLM or AI applications to production. Hands-on experience with agentic workflows and retrieval-augmented generation: prompt design, tool calling, vector search, and output evaluation. Strong Python, plus experience building REST APIs and data pipelines. Experience deploying on AWS with CI/CD, containers and automated testing. Experience working directly with business or clinical users to gather requirements and iterate on working software. Clear written and spoken communication, including demos to non-technical stakeholders. US work authorization and residence in the US.

Preferred qualifications: Experience with healthcare data and standards: HL7 FHIR, clinical notes, lab and imaging results, and EHR workflows (such as Epic or Oracle Health).Clinical NLP experience, such as entity extraction from clinical text. Experience with SAFe or Scrum and Atlassian tools. Familiarity with model evaluation and AI governance: model cards, bias testing, drift monitoring, human-in-the-loop review. Front-end experience (React or similar) and familiarity with the U.S. Web Design System.