Responsibilities:
Engineering
1. Work with Enterprise AI Engineers to support the development and automation of our internal technical products, including GenAI capabilities.
2. Join a diverse team working on some of Elanco’s exciting engineering projects, contributing to secure, reliable, and efficient solutions using modern technology.
3. Identify opportunities for continuous improvement within our core ecosystem to enhance application team and developer experience.
4. Collaborate with engineers to learn and contribute to our vision of secure, reliable, and efficient platforms.
5. Work cross-functionally, supporting both application teams and operational engineering teams.
Daily / Monthly Responsibilities
6. Assist with build and run activities for GenAI products, following incident processes and best practices.
7. Collaborate with distributed teams across the business, learning how to support AI/ML capabilities.
8. Contribute to code, support product building, maintenance, and documentation under guidance.
9. Participate as a member of a scrum team, helping to deliver technical solutions.
10. Support the automation of manual IT and business processes through technical contributions.
11. Help application teams resolve basic issues related to deployment and usage of engineering products.
12. Help work with distributed teams across the business on how to consume AI/ML
What You Need to Succeed (minimum qualifications):
13. Basicknowledge of natural language processing or AI technologies ()
14. Foundational knowledge in either Python/Typescript desirable
15. Operational experience taking internal products and ensuring they are well maintained, supported, and iterated upon.
16. Exposure to supporting products advantageous
17. Interest and basic knowledge of machine learning models ()
18. Familiarity working within an agile team.
What will give you a competitive edge (preferred qualifications):
19. Exposure to Cloud Native design principles (Microsoft Azure / Google Cloud preferred)
20. Basic experience with technical tools (ex. Terraform)
21. Awareness of cloud cognitive services (Azure Cloud Vision, Google Vision AI)
22. Familiarity with AI/Embeddings technologies (Google Matching Engine, Azure AI Studio, Vertex AI)
23. Introductory knowledge of modern application architecture methodologies
24. Experience (coursework or internship) related to digital platforms, integrations, release management, or data obfuscation
25. Understanding of “API-First” integration patterns and API ecosystem basics
26. Basic knowledge of authentication/authorization protocols/patterns
Additional Information:
27. Travel:0-10%
28. Location: Hook, UK - Hybrid Work Environment