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Ai Reliability Engineer Jobs in Alabama (NOW HIRING)

Continental

AI Solutions Developer

AL · On-site

AI Solutions Developer About Continental: Continental Aerospace Technologies™ has been a leader ... Collaborate with stakeholders to test, validate, and refine AI solutions for usability, reliability ...

Anduril Industries

Systems Engineer

Huntsville, AL · On-site

Anduril's family of systems is powered by Lattice OS, an AI-powered operating system that turns ... Basic knowledge of reliability engineering concepts and practices. * Experience with systems ...

Anduril Industries

Systems Engineer

Huntsville, AL · On-site

Anduril's family of systems is powered by Lattice OS, an AI-powered operating system that turns ... Basic knowledge of reliability engineering concepts and practices. * Experience with systems ...

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Ai Reliability Engineer information

What are the key skills and qualifications needed to thrive as an AI reliability engineer, and why are they important?

To thrive as an AI Reliability Engineer, you need a solid background in computer science or engineering, expertise in AI/ML concepts, and experience with software testing and reliability methodologies. Familiarity with tools like TensorFlow, PyTorch, CI/CD pipelines, and reliability testing frameworks, along with certifications in cloud platforms (e.g., AWS Certified Machine Learning), is highly valuable. Analytical thinking, problem-solving abilities, and strong collaboration skills set top performers apart in this role. These skills ensure robust, dependable AI systems that meet performance standards and maintain trust in critical applications.

What is the difference between Ai Reliability Engineer vs Data Scientist?

AspectAi Reliability EngineerData Scientist
Required CredentialsBachelor's or master's in CS, engineering, or related; certifications in AI/MLBachelor's or master's in CS, statistics, or related; certifications in data analysis or ML
Work EnvironmentTech companies, AI-focused teams, engineering departmentsResearch labs, tech firms, analytics teams
Employer & Industry UsageAI product development, machine learning systems, reliability testingData analysis, predictive modeling, business insights

While both roles involve AI and ML, Ai Reliability Engineers focus on ensuring AI system robustness and uptime, whereas Data Scientists analyze data to generate insights and models. The roles often collaborate but serve different primary functions within AI projects.

What is an AI reliability engineer?

AI Reliability Engineers are professionals responsible for ensuring that artificial intelligence systems function reliably, safely, and effectively over time. They work on monitoring AI models in production, identifying and mitigating potential failures, and improving the robustness of AI systems. Their tasks often include testing, validation, performance monitoring, and implementing best practices for maintaining AI infrastructure. By focusing on reliability, they help organizations deploy AI solutions that are dependable and trustworthy in real-world environments.

What are some common challenges AI reliability engineers face when ensuring model robustness in production environments?

Ai Reliability Engineers often encounter challenges such as monitoring AI model performance for drift or unexpected behavior, managing data quality issues, and implementing automated alerting systems for anomalies. In production, it's crucial to ensure that AI models operate consistently and remain reliable under varying conditions and data inputs. Collaborating closely with data scientists, software engineers, and DevOps teams is essential to address these challenges and to continuously improve model reliability and uptime.
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Ai Reliability Engineer jobs near you

AI Solutions Developer

Continental Aerospace Technologies Inc

Mobile, AL • On-site

Full-time

Re-posted 20 days ago

Job description

AI Solutions Developer

About Continental:

Continental Aerospace Technologies™ has been a leader in aviation innovation for more than 120 years, continually pushing the limits of general aviation and shaping the evolution of aircraft performance and reliability. Today, we are a global force with a full range of gasoline and Jet‑A engines, across three continents. Built on a legacy of engineering excellence, technological advancement, and a strong commitment to safety, Continental continues to deliver industry‑leading engine solutions while opening the door to exciting careers for those who want to help shape the future of flight.
At Continental, you’re not just joining an industry leading aviation company—you’re joining a team that truly loves what we do. Our T.E.A.M. values—Transparency, Efficiency, Accountability, and Morality—which guide how we work, collaborate, and support one another. We’re proud to foster an environment where every voice matters, every idea is valued, and every employee has room to grow. If you’re driven by progress and passionate about shaping the future, Continental Aerospace Technologies™ offers a career path that lets you grow and make a difference.

Position Summary:
  • Continental Aerospace Technologies is seeking an AI Solutions Developer to accelerate the automation of business processes using AI technologies within the Microsoft ecosystem, including Power Platform, Copilot, Azure AI, and Microsoft 365. This role will help expand delivery capacity, reduce manual effort, improve turnaround time and solution quality, and scale secure, maintainable AI-driven workflows across the organization.
  • The AI Solutions Developer will work cross-functionally with business stakeholders to identify automation opportunities, design practical AI-enabled solutions, and implement governed workflows that improve decision support, operational efficiency, and business process execution.
Key Responsibilities:
  • Design, build, and maintain AI-driven workflow automation solutions using Microsoft Power Platform, Copilot, Azure AI, and Microsoft 365.
  • Partner with business teams to identify, evaluate, and prioritize opportunities for AI-enabled process improvement.
  • Develop secure, scalable, and maintainable automation solutions that reduce manual effort and improve business turnaround time.
  • Integrate Microsoft 365, Azure AI, and Power Platform capabilities to support process improvement and decision support.
  • Translate business requirements into technical solution designs, prototypes, and production-ready workflows.
  • Collaborate with stakeholders to test, validate, and refine AI solutions for usability, reliability, and business value.
  • Apply governance, security, and maintainability principles when designing AI-powered workflows and integrations.
  • Document solution architecture, workflow logic, user guidance, and support procedures.
  • Monitor implemented solutions for effectiveness, adoption, and opportunities for enhancement.
  • Stay current with Microsoft AI, Copilot, Power Platform, and Azure AI capabilities and recommend practical applications for the organization.
Required Qualifications:
  • Experience designing or developing workflow automation, business applications, or AI-enabled productivity solutions.
  • Working knowledge of Microsoft Power Platform, such as Power Automate, Power Apps, Power BI, or Dataverse.
  • Familiarity with Microsoft 365 tools and how they support business process automation.
  • Understanding of AI concepts, prompt design, agentic harnesses, MCP development, solution governance, and responsible use of AI technologies.
  • Ability to gather requirements from business users and translate them into practical technical solutions.
  • Strong analytical, problem-solving, communication, and documentation skills.
  • Ability to work collaboratively with technical and non-technical stakeholders.
Preferred Qualifications:
  • Experience with Azure services, Copilot Studio, Microsoft Graph, SharePoint, Teams, or other Microsoft 365 integrations.
  • Experience building automated approval flows, reporting workflows, document processing solutions, or AI-assisted business processes.
  • Experience integrating AI-enabled workflows with enterprise systems, financial systems, databases, APIs, and other business applications.
  • Working knowledge of SQL for data access, reporting, workflow automation, and business process integration.
  • Familiarity with API design, REST-based integrations, and connecting applications or services across enterprise platforms.
  • Experience with Microsoft-stack development (Microsoft 365 Agents SDK) is preferred, particularly for custom applications, integrations, or extensions beyond low-code/no-code solutions.
  • Familiarity with Python-based machine learning, applied AI development, or data analysis is a plus, especially where used to support automation, decision support, or process improvement.
  • Familiarity with enterprise security, data governance, role-based access, and lifecycle management for business applications.
  • Experience supporting adoption, training, or change management for new digital tools.
  • Experience in manufacturing, aerospace, engineering, business development, financial systems, or operational process improvement environments.
Knowledge, Skills, and Abilities:
  • Strong understanding of Microsoft ecosystem tools and how they can be combined to automate business processes.
  • Ability to evaluate business workflows and identify where AI, automation, integrations, or data-driven solutions can add measurable value.
  • Ability to build solutions that are maintainable, secure, scalable, and aligned with organizational governance expectations.
  • Ability to integrate AI-enabled workflows with Microsoft 365 services, enterprise systems, financial systems, SQL databases, APIs, and other business applications.
  • Working knowledge of API concepts, data flows, system integrations, and secure information exchange between platforms.
  • Ability to apply SQL, reporting, and data analysis concepts to support workflow automation, decision support, and process improvement.
  • Ability to leverage low-code/no-code tools, AI services, and, where appropriate, custom development approaches to deliver practical business solutions.
  • Strong communication skills with the ability to explain technical concepts to business stakeholders.
  • Ability to manage multiple automation opportunities from intake through delivery.
  • Attention to detail when documenting requirements, workflows, integrations, testing outcomes, and support processes.
  • Continuous improvement mindset and willingness to learn emerging AI, automation, integration, and Microsoft ecosystem capabilities.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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