What You’ll Do

Built and deployed a reusable AI-powered service or integration that enabled a business team to automate a critical workflow
Designed and implemented connectors between AI systems and internal or third-party platforms such as Salesforce or Workday
Partnered with stakeholders to identify a high-impact opportunity and translated it into a scalable internal tool or workflow
Improved reliability and performance of an existing AI-enabled system by debugging across APIs, services, and infrastructure
Evaluated new AI tools or frameworks and contributed to decisions on how they can be securely adopted at scale
Partnered with InfoSec to ensure systems meet security, compliance, and governance standards
Led a working session or demo to help teams understand and adopt new AI-enabled capabilities
Built reusable components, services, or patterns that make it easier for other teams to leverage AI

What You’ll Need

5+ years of experience in software engineering or related technical roles
Strong hands-on experience building and shipping production systems using modern programming languages and frameworks
Experience working with AI technologies such as LLMs and an understanding of how to integrate them into applications and workflows
Strong experience with REST APIs, microservices, and system integrations
Experience building internal tools, platforms, or shared services used by multiple teams
Familiarity with authentication and security patterns such as OAuth, JWT, and IAM
Ability to debug across full-stack systems including services, APIs, workflows, and cloud infrastructure
Strong communication skills and the ability to work effectively with both technical and non-technical stakeholders

Experience building AI-powered applications using tools such as OpenAI, Claude, or similar platforms
Experience with enterprise automation or integration platforms
Familiarity with cloud platforms such as AWS, Azure, or GCP
Experience with data governance, security, and compliance in enterprise environments