Senior GenAI Platform Engineer for Healthcare

Baylor Scott & White Health; Dallas (TX); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Health benefits

401k match

Tuition reimbursement

PTO from day 1

Job summary

Baylor Scott & White Health seeks a senior backend engineer to build a production-grade GenAI platform for patient-facing and enterprise experiences. You will design and operate backend AI services, agentic workflows, and secure clinical integrations using Python, FastAPI, and MCP tool servers.

You will own end-to-end delivery, enforce PHI protection, and collaborate with product, security, architecture, and clinical teams to ship safe AI capabilities at scale.

Qualifications

• 7+ years of professional software development experience.
• Strong production experience with Python, asynchronous programming, backend APIs, and service-oriented architecture.
• Hands-on experience building GenAI applications with Google ADK 2.x or similar agent orchestration frameworks.
• Demonstrated understanding of LLM tool calling, multi-agent workflows, structured outputs, RAG, prompt engineering, and AI safety/guardrail patterns.
• Experience integrating with LLM providers such as Google Gemini/Vertex AI, OpenAI, Anthropic, or equivalent platforms.
• Experience with FastAPI, pytest, Docker, CI/CD workflows, and containerized production deployments.
• Strong understanding of API security, JWT/OAuth, delegated authorization, secrets management, and secure service-to-service communication.
• Ability to design safe integration patterns for healthcare data, clinical systems, or other sensitive regulated environments.
• Experience with cloud-native services in Azure and/or Google Cloud.
• Strong debugging, testing, and operational problem-solving skills.
• Ability to work with high ownership in a small, fast-moving engineering team.
• Strong communication skills and ability to collaborate across engineering, architecture, security, product, and clinical stakeholders.

Responsibilities

• Design, implement, and maintain backend AI services using Python 3.12+, async service patterns, and frameworks such as FastAPI, Google ADK, and FastMCP.
• Develop and operate agentic GenAI workflows using Google ADK 2.x as a primary orchestration framework.
• Build MCP tool servers and domain-specific tools for healthcare workflows such as care tasks, medications, scheduling, patient profile lookup, clinical record retrieval, and EHR/FHIR-backed experiences.
• Integrate LLM providers and GenAI toolkits including Google Gemini/Vertex AI, OpenAI, Anthropic, and related orchestration frameworks where appropriate.
• Implement prompt engineering, RAG, structured output validation, tool selection patterns, memory strategies, and AI guardrails to support safe and reliable model behavior.
• Design secure clinical integration boundaries for FHIR, EHR, user profile, scheduling, and other healthcare systems.
• Protect PHI and sensitive credentials through secure JWT/OAuth flows, delegated authorization, token forwarding, encryption, redaction, and audit-safe logging.
• Leverage cloud services such as Azure App Configuration, Key Vault, Cosmos DB, Event Hubs, Application Insights, and Google Cloud services such as Vertex AI/Gemini and Cloud Run.
• Build observability, telemetry, evaluation, and impact-reporting capabilities for AI systems and AI-assisted engineering workflows.
• Author and maintain automated tests using pytest and support linting, type-checking, CI/CD, and containerized deployments.
• Collaborate with product, architecture, security, clinical, platform, DevOps, and application teams to deliver safe AI capabilities through well-defined HTTP/MCP contracts.
• Participate in architecture discussions, code reviews, production support, operational readiness, and incident response.

Skills

Python

GenAI

Backend APIs

FastAPI

OAuth/JWT

Tools

FastAPI

pytest

Docker

CI/CD

Azure

Vertex AI

Job description

Baylor Scott & White Health seeks a senior backend engineer to build a production-grade GenAI platform for patient-facing and enterprise experiences. You will design and operate backend AI services, agentic workflows, and secure clinical integrations using Python, FastAPI, and MCP tool servers.

You will own end-to-end delivery, enforce PHI protection, and collaborate with product, security, architecture, and clinical teams to ship safe AI capabilities at scale.