Senior AI Engineer

Procter & Gamble•Cincinnati, OH

3d•$132,200 - $165,300•Hybrid

About The Position

The Senior AI Engineer is part of P&G’s Data, Analytics, and AI job family, which transforms complex data into actionable insights. The role partners with Data Science and Business teams to develop, operationalize, integrate, and scale algorithmic products. It includes evaluating models and technologies through proofs of concept and experiments, writing high-quality tested code, contributing to reusable libraries and open-source projects in line with P&G IT policies, and building data models, model features, quality tests, ETL/ELT pipelines, and distributed architectures. The engineer deploys algorithmic products across cloud environments using cloud-native services. The position works with Data Scientists, Analysts, and other AI Engineers on advanced analytics, applications, and analytical algorithms. It develops data-sourcing applications using Python and SQL, optimizes analytical solutions at scale, supports multi-cloud environments, and operationalizes machine-learning models as part of IT solutions and business processes. The role also applies DevOps, Agile, and CI/CD practices; improves code reuse and platform engineering; troubleshoots infrastructure issues; and strengthens AI Engineering practices by developing prototypes, improving architectures, and coaching or teaching others. The position is based at the Cincinnati general offices and requires the ability to work a hybrid schedule in the Cincinnati, Ohio office. Candidates should be prepared to consider relocation opportunities throughout their career as business needs and development opportunities arise. Immigration sponsorship is not available for this role.

Requirements

Bachelor’s or master’s degree in Computer Science, Software Engineering, or a related field.
At least 5 years of proven experience with Python and SQL, data modelling, and the design, development, and deployment of Data and Analytics products.
Experience with Agile and DevOps methodologies and relevant tools, such as Jira, GitHub Actions, unit testing and mocking, static code analysis, and source control management tools such as GitHub.
Knowledge of Azure cloud infrastructure, including load balancing, autoscaling, firewalls, and authentication.
Knowledge of Databricks.
Knowledge of logging and monitoring technologies, such as Logstash, Grafana, or Kibana, depending on needs.
Knowledge of CI/CD processes and development using GitHub Actions and GitHub.
Knowledge of infrastructure build tools and languages, including Terraform and Ansible.
Strong written and verbal communication in English.
Ability to work a hybrid schedule in the Cincinnati, Ohio office.

Responsibilities

Partner with Data Science and Business teams to develop, operationalize, integrate, and scale algorithmic products.
Conduct proofs of concept and experiments to evaluate models, technologies, and new analytical algorithms and applications.
Develop high-quality, standards-compliant, tested code and contribute code and tools to reusable libraries, repositories, and open-source projects in line with P&G IT policies.
Develop data models, model features, data quality tests, ETL/ELT pipelines, and distributed computer architectures.
Deploy algorithmic products across cloud environments using cloud-native services.
Work with Data Scientists, Analysts, and peer AI Engineers on advanced analytics use cases.
Prepare data models and quality checks and optimize analytical solutions at scale.
Design and develop applications that source data from various systems using Python and SQL.
Support solutions in multi-cloud environments and services, including Azure and/or GCP.
Apply DevOps and Agile practices, use CI/CD tools, and increase reuse of internal code libraries and design patterns.
Operationalize machine-learning models as integral elements of IT solutions and business processes.
Implement platform engineering practices that make cloud infrastructure easier for data scientists and model developers to use.
Troubleshoot infrastructure issues to support critical Artificial Intelligence products at P&G.
Develop proactive incident detection systems using multiple data sets and real-time data-stream analysis.
Create proofs of concept or prototypes for new features and solutions, recommend and implement architecture improvements, and strengthen DevOps practices through coaching and teaching.