Lead Engineer – Enterprise AI 

Responsibilities: 

Engineering 

• Work with Principal Platform Engineer and Senior Product Owner to help drive direction of platform and automation capabilities including our internal technical products related to GenAI capabilities. 

• Work with a diverse team on some of Elanco’s most exciting engineering initiatives helping drive secure, reliable, and efficient using the latest technology. 

• Stay abreast of the latest AI research, trends, and technologies, and apply this knowledge to drive continuous improvement and innovation within the team. 

• Look for continuous improvement opportunities in our core ecosystem identifying new ways to enhance application team and developer experience. 

• Bring your expertise into a team of talented engineers and continually help shape where the team can help to better enable our secure, reliable, efficient vision. 

• Follow the value mentality with opportunity to work across the engineering team helping to ‘walk in the shoes’ of application teams as well as operational engineering teams. 

• Communicate progress, results, and insights to management and other stakeholders. 

• Strong understanding of MLops principles and practices 

Daily / Monthly Responsibilities 

• Build and run responsibilities for GenAI ensuring robust support folding into standard incident processes as the products mature. 

• Help work with distributed teams across the business on how to consume AI/ML capabilities. 

• Hands on code, build, govern and maintain. 

• Working as part of a scrum team, deliver high quality technical deliverables. 

• Designing and building solutions to support the automation of manual IT and business processes. 

• Continually modernise software development processes using Continuous Integration and Continuous Delivery (CI/CD) techniques to ensure efficient and high-quality delivery. 

• Establish strong partnerships with key service integrators (vendors), helping to support the adoption of automation capabilities. 

• Establish a strong partnership with our application health program and Information Security, helping to identify opportunities and mitigate risks. 

• Coach and mentor junior engineers, members of our student program to help build a strong connected organisation.  

• Supporting application teams, internal and external, helping to resolve barriers related to building, deployment, and utilisation of engineering products. 

Basic Qualifications:  

Must have experience in the following areas:

• Minimum 2+ years of hands-on experience in Generative AI and LLMs. An overall 8+ years of experience as Software Engineer. 

• Proficiency in programming languages such as Python, TensorFlow, PyTorch, and other AI/ML frameworks. 

• Strong understanding of MLops principles and practices 

• Ability to design and implement complex ML systems 

• Strong understanding of neural networks, natural language processing (NLP), computer vision, and other AI domains. 

• Experience with cloud platforms and AI tools (e.g., Google Cloud, Azure). 

• Familiarity with natural language processing or AI technologies (e.g LLMs such as ChatGPT or BARD, Embeddings, Prompt Engineering) 

• Experience with data pipelines and preferably processing of documents (e.g using Google Cloud Fusion/Azure Data Factory) 

• Demonstrated success in deploying AI solutions in real-world applications. 

• Work closely with product managers, data scientists, software engineers, and other stakeholders to integrate AI solutions into existing and new products. 

• Stay abreast of the latest AI research, trends, and technologies, and apply this knowledge to drive continuous improvement and innovation within the team. 

• Strong background in either Python/Typescript 

• Operational experience taking internal products and ensuring they are well maintained, supported, and iterated upon. 

• Experience working with technical and non-technical team members to encourage adoption of new versions of software or products.  

• Working within a DevOps team including modern software development practices, covering Continuous Integration and Continuous Delivery (CI/CD), Test-Driven Development (TDD), SDLC, etc. 

• Familiarity working within an agile team. 

Nice to Have: 

Experience in some of the following areas:

• Experience working with Cloud Native design patterns, with a preference towards Microsoft Azure / Google Cloud. 

• Hands-on Technical experience with at least some of our core technologies (Terraform, Ansible, Packer). 

• Working with cloud cognitive services (e.g Azure Cloud Vision or Google Vision AI) 

•  Working with AI/Embeddings technologies (e.g Google Matching Engine, Azure AI Studio, Vertex AI) 

• Experience working in/with an infrastructure team advantageous.  

• Experience with modern application architecture methodologies (Service Orientated Architecture, API-Centric Design, Twelve-Factor App, FAIR, etc.). 

• Experience supporting digital platforms, including Integrations, Release Management, Regression Testing, Integrations, Data Obfuscation, etc. 

• Knowledge of Azure Data Factory/ GCP Cloud Data Fusion, Microsoft Azure Machine Learning or GCP Cloud ML Engine, Azure Data Lake, Azure Databricks or GCP Cloud Dataproc. 

• Experience scaling an “API-Ecosystem”, designing, and implementing “API-First” integration patterns. 

• Experience working with authentication and authorisation protocols/patterns. 

• Experience with AI security, model evaluation, and safety.