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# Senior AI/ML Engineer

- **Company:** Yantran Llc
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Application Performance Management, Microsoft Azure, Code Review, Continuous Integration, Github, Medical Software, Python (Programming Language), Key Management, Machine Learning, OAuth, Software Architecture, OpenAI, Software Safety, Service Development Studio, Software Engineering, Systems Integration, TypeScript, Azure Service Bus, Datadog, Scripting, ReactJS, Fast Healthcare Interoperability Resources, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Apigee, Backend, Fastapi, Pytest, Containerization, Health Level Seven International, Cosmos DB, PydanticAI Framework, Virtual Agents, Artificial Intelligence Governance, Docker, Key Vault
- **Published:** October 22, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-ai-ml-engineer-dallas-tx--0dade4f6-f9b4-403a-9a55-a04c2c543284

## About the Role

Artificial Intelligence (AI), Legal, Disability Insurance, Life Insurance, Healthcare Software, System Integration (SI), Artificial Intelligence (AI), Healthcare, Application Programming Interface (API), Python Programming/Scripting Language, A minimum of five years of professional software development experience.
Strong proficiency in Python, with demonstrated production experience using FastAPI or comparable asynchronous frameworks.
Hands on experience with LLM orchestration frameworks such as LangGraph, PydanticAI, or equivalent systems.
Solid understanding of prompt engineering, retrieval augmented generation (RAG) patterns, and AI guardrails.
Experience with Azure cloud services, including Cosmos DB, Azure Key Vault, and App Configuration.
Familiarity with Docker, CI/CD Pipeline (e.g., GitHub Actions), and containerized deployments.
Strong knowledge of JWT/OAuth authentication mechanisms and Securing Apigee APIs best practices.
Ability to operate effectively within a small, fast paced team environment with a high degree of ownership.
Preferred Skills
Experience within the healthcare domain, including HIPAA Regulation, HL7 (Health Level Seven), and FHIR (Fast Healthcare Interoperability Resources) integrations.
Experience with PydanticAI and structured LLM output validation.
Familiarity with OpenTelemetry and observability tooling.
Exposure to React and TypeScript for limited full stack contributions.
*** is an Equal Employment Opportunity employer. We promote and support a diverse workforce at all levels of the company. All qualified applicants will receive consideration for employment without regard to race, religion, color, sex, age, national origin, or disability. All applicants will be evaluated solely based on their ability, competence, and performance of the essential functions of their positions with or without reasonable accommodations. Reasonable accommodation also are available in the hiring process for applicants with disabilities. Candidates can request a reasonable accommodation by contacting the company ADA Coordinator at

## Description

We are seeking an experienced Senior Backend / AI Developer to join a dynamic engineering team responsible for developing and scaling a production grade healthcare conversational AI platform. This role will focus on backend service development, AI agent workflows, and system integrations that support patient facing conversational experiences. The ideal candidate will have a strong background in AI/ML engineering, particularly in the context of healthcare applications.
Responsibilities
Design, develop, and maintain backend APIs and services using Python 3.12+ and FastAPI.
Develop and enhance multi agent AI orchestration workflows using LangGraph, LangChain, or PydanticAI.
Integrate and optimize large language model providers, including OpenAI, Anthropic, and Google GenAI.
Work with Azure services such as Cosmos DB, App Configuration, Key Vault, Event Hubs, and Application Insights.
Develop and maintain task handlers for domain specific workflows (e.g., care tasks, medications, scheduling).
Implement input and output guardrails, prompt engineering techniques, and AI safety patterns.
Collaborate on architectural decisions, code reviews, and production support activities.
Develop and maintain automated test suites using pytest.