Senior Engineer Gen AI

Role Title:

Responsibilities:

• Work with Principal Platform Engineer 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 Elancos most exciting engineering initiatives helping drive secure, reliable, and efficient using the latest technology.
• 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.

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 one year of hands-on experience in Generative AI and an overall 5+ years of experience as Software Engineer.
  o Working within a DevOps team including modern software development practices, covering Continuous Integration and Continuous Delivery (CI/CD), Test-Driven Development (TDD), SDLC, etc.o Familiarity working within an agile team.o Developing machine learning models (Python or TensorFlow)
  o Familiarity with natural language processing or AI technologies (e.g LLMs such as ChatGPT or BARD, Embeddings, Prompt Engineering)
  o Experience with data pipelines and preferably processing of documents (e.g using Google Cloud Fusion/Azure Data Factory)o Strong background in either Python/Typescripto Operational experience taking internal products and ensuring they are well maintained, supported, and iterated upon.o Experience working with technical and non-technical team members to encourage adoption of new versions of software or products.

  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.
  o Hands-on Technical experience with at least some of our core technologies (Terraform, Ansible, Packer).o Working with cloud cognitive services (e.g Azure Cloud Vision or Google Vision AI)
  o Working with AI/Embeddings technologies (e.g Google Matching Engine, Azure AI Studio, Vertex AI)
  o Experience working in/with an infrastructure team advantageous. o 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.
• Familiarity with big data technologies and distributed computing frameworks, such as Hadoop, Spark, or Apache Flink.
• Experience scaling an API-Ecosystem, designing, and implementing API-First integration patterns.
• Experience working with authentication and authorisation protocols/patterns.

Other Information: