Teams at Skan AI

Embed with enterprise customers to understand workflows, specify agent behavior, build and integrate AI agents, configure guardrails and human oversight, validate performance, conduct user acceptance and shadow-mode testing, lead production go-lives, and measure business impact. The role requires strong Python and SQL, cloud experience, AI or data/ML product development, and excellent customer communication.

Embed with enterprise customers to understand workflows, specify agent behavior, author decision logic, build and integrate AI agents, and deploy them with governance and human oversight. Responsibilities include calibration, user acceptance testing, shadow-mode validation, production launches, monitoring, and measuring business impact. The role requires strong Python and SQL, cloud experience, production or prototype AI/ML delivery, and excellent customer communication.

Designs and maintains CI/CD pipelines, infrastructure-as-code templates, deployment tooling, and DevSecOps controls for cloud, on-premises, and hybrid customer environments. Automates provisioning, upgrades, patching, monitoring, and operational reporting while supporting Systems Engineering and collaborating with SRE. The role also tracks deployment metrics, remediates pipeline failures and configuration drift, supports change management, documents processes, and contributes to agentic workflow automation.