AI Engineer

Global Medical Response

• $110K — $130K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in AI and machine learning engineering.
  • Strong fundamentals in software engineering and development practices.
  • Proficiency in Azure AI tools and SDLC methodologies.
  • Experience with multi-cloud environments, preferably AWS and GCP.
  • Ability to collaborate effectively with cross-functional teams.

Responsibilities

  • Design and develop AI-enabled solutions like machine learning models and workflow automations.
  • Build integrations between AI systems and enterprise applications using secure methods.
  • Develop and maintain training and evaluation patterns for AI models.
  • Create reusable assets, such as prompt libraries and deployment scripts.
  • Collaborate with stakeholders to clarify requirements and deliver solutions.
  • Participate in architecture and peer reviews, ensuring quality and compliance.
  • Monitor performance and troubleshoot issues in deployed AI solutions.

Benefits

  • Comprehensive health benefits including medical, dental, and vision.
  • Flexible work arrangements with hybrid options.
  • Professional development opportunities to enhance skills.
  • Access to the latest AI engineering tools and cloud services.
  • Supportive environment emphasizing responsible AI practices.
Full Job Description
Job Description

AI Engineer

Hybrid - Dallas/Lewisville Area

IMMEDIATELY HIRING! FULL-TIME AI Engineer

We are seeking a skilled and motivated AI Engineer to design, build, test, and deploy AI and machine learning solutions that address real business problems. This role is a hands-on engineering position focused on developing production-ready AI capabilities, integrating models and agents with enterprise systems, and collaborating with cross-functional partners to deliver secure, scalable, and responsible AI solutions. The ideal candidate brings strong software engineering fundamentals, practical AI/ML experience, and the ability to translate business needs into working technical solutions.

Responsibilities:
  • Design, develop, test, and deploy AI-enabled solutions, including machine learning models, generative AI applications, copilots, agents, and workflow automations.
  • Build integrations between AI solutions and enterprise systems using APIs, connectors, governed data sources, and secure authentication patterns.
  • Develop model training, evaluation, prompt engineering, grounding, and retrieval-augmented generation patterns as appropriate for business use cases.
  • Create reusable technical assets such as prompt libraries, agent templates, automation patterns, deployment scripts, and solution documentation.
  • Collaborate with product owners, business stakeholders, architects, data teams, and security partners to clarify requirements and deliver practical AI solutions.
  • Participate in architecture reviews, peer reviews, testing, deployment planning, and change management processes.
  • Monitor AI solution performance, troubleshoot production issues, and support continuous improvement of deployed capabilities.
  • Apply responsible AI, privacy, security, and compliance standards throughout solution design, implementation, and support.
  • Stay current on AI engineering tools, cloud services, model capabilities, and industry practices, and apply relevant learnings to improve solution delivery.


Key Technologies:
  • Azure AI tools such as Foundry, Azure Databricks, AI Search, or similar
  • SDLC and Agentic Development tooling such as Azure Dev Ops, Git Hub, Git Hub Copilot, Claude Code, Codex
  • Multi-Cloud - Experience developing for Multi-Cloud or with similar tooling across AWS or GCP


More Information about this Job

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