Principal Engineer - Gen Ai

Overview

Elanco is a global leader in animal health, dedicated to innovation and delivering products and services to prevent and treat disease in farm animals and pets. We strive to enrich life through Food and Companionship and to Go Beyond for Animals, Customers, Society and Our People. We foster a diverse and inclusive work environment and value new ways of thinking. We are building a modern technology stack as a stand-alone company and are establishing engineering capabilities to deliver customer value faster.

This role is part of our enterprise platform engineering team with a focus on GenAI capability and implementation within Elanco. You will work at the cutting edge of GenAI strategy, build and support our own implementations, and contribute to the growth of a highly skilled engineering organization. To be successful, you should be highly motivated, innovative, and able to articulate complex technical topics, collaborate with external partners, and ensure quality delivery.

• Engineering:
  Collaborate with the Principal Platform Engineer and Senior Product Owner to steer platform and automation capabilities, including internal technical products related to GenAI.
• Work with a diverse team on exciting engineering initiatives to drive secure, reliable, and efficient solutions using the latest technology.
• Stay current with AI research, trends, and technologies and apply this knowledge to drive continuous improvement and innovation.
• Identify continuous improvement opportunities in the core ecosystem to enhance application team and developer experience.
• Contribute expertise as part of a team of engineers to shape how the team enables secure, reliable, and efficient solutions.
• Align with value-driven thinking and collaborate across the engineering team and with application and operational engineering groups.
• Communicate progress, results, and insights to management and other stakeholders.
• Apply a strong understanding of MLops principles and practices.
• Daily/Monthly responsibilities: build and run GenAI capabilities, integrate with incident processes, and collaborate with distributed business teams to adopt AI/ML capabilities.
• Hands-on coding, governance, and maintenance; work within a scrum framework to deliver high-quality technical outputs.
• Design and build solutions to automate manual IT and business processes.
• Modernize software development processes with CI/CD to ensure efficient, high-quality delivery.
• Establish partnerships with key service integrators and support automation capability adoption.
• Collaborate with the application health program and Information Security to identify opportunities and mitigate risks.
• Coach and mentor junior engineers and participants in the student program to build a connected organization.
• Support application teams (internal and external) to resolve barriers related to building, deployment, and utilization of engineering products.

• Minimum 2+ years of hands-on experience in Generative AI and LLMs; overall 8+ years of software engineering experience.
• Proficiency in programming languages such as Python, Tensor Flow, PyTorch, and other AI/ML frameworks.
• Strong understanding of MLops principles and practices.
• Ability to design and implement complex ML systems and a solid grounding in neural networks, NLP, computer vision, and related AI domains.
• Experience with cloud platforms and AI tools (e.g., Google Cloud, Azure).
• Familiarity with NLP or AI technologies (e.g., LLMs, embeddings, prompt engineering).
• Experience with data pipelines and document processing (e.g., Google Cloud Fusion, Azure Data Factory).
• Proven success deploying AI solutions in real-world applications and collaborating with product managers, data scientists, software engineers, and other stakeholders to integrate AI into products.
• Stays current with AI research and applies it to drive improvement and innovation.
• Strong programming background in Python/Type Script; operational experience maintaining internal products.
• Experience working with technical and non-technical team members to drive adoption of new software versions.
• Experience with in a Dev Ops context (CI/CD, TDD, SDLC) and in agile environments.

• Experience with Cloud Native design patterns, especially Microsoft Azure or Google Cloud.
• Hands-on experience with core technologies (Terraform, Ansible, Packer).
• Experience with cloud cognitive services (e.g., Azure Cloud Vision, Google Vision AI) and AI/Embeddings (e.g., Google Matching Engine, Azure AI Studio, Vertex AI).
• Experience with modern application architecture (SOA, API-Centric Design, Twelve-Factor App, FAIR).
• Experience supporting digital platforms, including integrations, release management, regression testing, data obfuscation, etc.
• Knowledge of Azure Data Factory / GCP Cloud Data Fusion, Azure ML, GCP ML Engine, Azure Data Lake, Databricks, or GCP Dataproc.
• Experience scaling an API ecosystem and…