About the Role
The Corporate AI Engineer is a hands-on technical role responsible for building, integrating, and operationalizing AI-enabled solutions across the enterprise. This role focuses on delivery and execution, turning prioritized AI use cases into secure, scalable, production-ready capabilities that drive measurable business value. As a core AI-solution delivery member of the Enterprise Architecture team, the Corporate AI Engineer partners closely with IT, Security, Data, and Business teams to move AI solutions from idea to pilot to measurable enterprise impact. Join us if you are passionate about leveraging AI to drive meaningful outcomes and if you thrive in a growing, collaborative and innovative environment.
What you'll do
- Design, build, and deploy AI-enabled solutions aligned to prioritized use cases.
- Implement AI workflows, integrations, and automations across enterprise platforms (e.g., Microsoft 365, Salesforce, ServiceNow) using best-in-breed AI technology from Anthropic, OpenAI, etc.
- Translate architectural designs and business requirements into working AI solutions, including prompt engineering, orchestration logic, retrieval augmented generation (RAG) patterns.
- Integrate AI solutions with enterprise data sources and systems of record, ensuring data quality, accuracy, and appropriate access.
- Own operational readiness of AI solutions, including monitoring, logging, performance tuning, and ongoing optimization.
- Partner with Security, Privacy, and IT teams to ensure AI solutions comply with enterprise governance, risk, and compliance requirements.
- Develop and maintain technical documentation, runbooks, and reusable implementation patterns.
We’re looking for someone with
- 4+ years of experience in software engineering, platform engineering, data engineering, application management, or a similar hands-on technical role.
- Demonstrated experience building, integrating, or operating production systems in an enterprise environment.
- Hands-on experience implementing AI-enabled solutions, including generative AI concepts such as prompt engineering, embeddings, or RAG with best-in-class AI technologies from OpenAI, Anthropic, ServiceNow, Microsoft, etc.
- Experience working with APIs, integrations, MCPs, and enterprise SaaS platforms.
- Working knowledge of AI-related risks, including data security, privacy, model limitations, and cost considerations.