AI Software Reliability Engineer

at  Lilly

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

COME SHAPE THE FUTURE OF OUR INDUSTRY BY BRINGING ARTIFICIAL INTELLIGENCE CAPABILITIES TO LIFE!

Digital Core Tech@Lilly is actively looking for an AI Software Reliability Engineer to spearhead our efforts in enhancing the robustness and dependability of AI-driven systems across multiple processes and systems in pharma. In this role, you’ll be at the heart of ensuring that AI technology is not only innovative but also reliable and safe for users across various domains. Are you passionate about artificial intelligence and the impact it can have across an entire industry? Are you a change agent who can influence organizations? If so, bring YOUR skills and talents to Lilly where you’ll have the chance to create an impact on the lives of patients!

HOW YOU WILL SUCCEED:

Analytical Expertise and Innovation: Leverage strong analytical skills to tackle complex problems related to AI reliability, deploying innovative solutions that enhance system performance and robustness.
Technical Proficiency: Utilize your deep technical knowledge in software engineering, AI technologies, and reliability engineering principles to drive the development of reliable AI applications.
Effective Collaboration and Communication: Work effectively across multidisciplinary teams, communicating complex reliability concepts in an understandable manner to both technical and non-technical stakeholders.
Proactive Problem-Solving: Anticipate potential reliability issues in AI systems and address them proactively, employing a preventative approach to system design and maintenance.
Continuous Improvement: Embrace a culture of continuous improvement, constantly seeking ways to enhance the reliability and performance of AI systems. Engage in ongoing learning to stay at the forefront of AI reliability engineering.

YOUR BASIC QUALIFICATIONS:

• Bachelor’s degree in computer science, engineering, mathematics, or a related field.
• 2+ years of experience in software engineering with a specific focus on reliability and performance aspects.
• Experience with programming languages such as Python, Java, or C++, especially in the contexts of software troubleshooting, testing, deployment, and error handling.

AI Reliability Strategy and Implementation: Develop and implement strategies to enhance the reliability, performance, and security of AI-driven systems, employing best practices in software engineering and reliability principles. Collaborate with AI researchers and software developers to integrate reliability into every phase of the AI development lifecycle.
Incident Management and Resolution: Lead efforts to identify, diagnose, and resolve system outages or disruptions, employing a comprehensive understanding of AI technologies and software infrastructure. Utilize data-driven approaches to analyze root causes and implement preventative measures. Lead and work with third party team members in the process.
Performance Optimization: Monitor and optimize the performance of AI systems, ensuring they operate efficiently under varying conditions. Implement robust testing frameworks to simulate different scenarios and stress tests for AI models.
Continuous Integration and Deployment (CI/CD) for AI: Enhance and maintain CI/CD pipelines for AI systems, ensuring smooth and reliable deployment of AI models and applications. Work closely with development teams to automate reliability checks and balances within the deployment process.
Reliability and Security Advocacy: Champion best practices in AI reliability and security within the organization. Provide guidance and training to development teams on creating more reliable and secure AI solutions. Stay abreast of emerging trends and technologies in AI reliability and cybersecurity.