AI Solutions Engineer, Life Sciences

Role overview Design and deliver secure integrations that let AI tools work with approved client data and systems in biotech and pharmaceutical environments. The role covers connectors, identity and access controls, and practical AI tools, with direct collaboration with client IT and security teams. You’ll also review a junior developer’s code and help set engineering standards.

Responsibilities - Build MCP servers and connectors that provide controlled AI access to client platforms and data. - Configure identity and access for AI deployments, including single sign-on, SCIM provisioning, permissions, and audit logging. - Implement data protections such as sensitivity labels, encryption, read-only access, retention, and log export. - Develop document pipelines, retrieval over approved materials, agents, and automations. - Explain technical designs to client IT, security, and quality teams, and prepare approval documentation. - Review junior developer code and establish engineering practices.

Requirements - At least five years building and operating production software or IT systems. - Shipped integrations involving APIs, identity standards such as OAuth, OIDC, SAML, or SCIM, and a major cloud platform. - Strong Python or TypeScript skills. - Hands-on work with LLM APIs, MCP, or agents, and regular use of AI coding tools. - Ability to communicate designs to both technical teams and non-technical leaders. - Excellent spoken and written English, plus availability during North American Eastern and Pacific business hours.

Nice to have - Experience in life sciences, healthcare, or another regulated industry.

Benefits and work setup - Fully remote role based in Canada, with flexible hours. - Salary range of CAD 125,000–155,000. - Work on client systems from design through production, collaborating directly with the founder and security lead. - Paid access to current AI tools.