
Lead Engineer – Enterprise AI
- United Kingdom
- Permanent
- Full-time
- 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
- 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.
- 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.
- 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.
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