Lead Platform Engineer - Gen AI

Responsibilities:

Engineering

Work with Principal Platform Engineer and Senior Product Ownerto 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.

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.

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

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

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

Familiarity with natural language processing or AI technologies ()

Experience with data pipelines and preferably processing of document)

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.

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 atleast some of our core technologies (Terraform, Ansible, Packer).

Working with cloud cognitive services ()

Working with AI/Embeddings technologies ()

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.

Other Information:Occasional travel may be required.