Senior Software Engineer, AI Automation

Role overview Lead the engineering of AI agents and automation workflows that reduce manual work across internal business teams. You’ll turn complex, sometimes ambiguous processes into reliable software, establish reusable patterns, and guide systems from early experimentation into production. The role calls for strong judgment about evaluation, permissions, human review, and operational safety.

Responsibilities - Design and deliver AI agents, reusable skills, and automation workflows for internal teams. - Convert complex processes, judgment calls, and edge cases into maintainable software. - Build integrations between agents and systems of record using MCP or similar tool integration frameworks. - Set architecture, interfaces, data contracts, and operating standards for production AI systems. - Define evaluation methods, quality baselines, and release criteria; use results to guide deployment and iteration. - Implement controls for permissions, monitoring, auditability, human review, failure containment, and rollback. - Partner with data and business stakeholders, mentor technical colleagues, and document systems and operating practices.

Requirements - At least seven years of hands-on software engineering experience, including recent delivery of LLM-backed applications used by real users. - Experience taking AI agents or multi-step automation from prototype through production operation. - Strong Python and practical SQL skills, including work with production data models. - Deep familiarity with prompting, tool use, agent workflows, structured outputs, error handling, and deployment. - Experience integrating with business-critical systems and applying sound evaluation, reliability, and safety practices. - Production engineering fundamentals across Git, CI/CD, containers, deployment, monitoring, testing, permissions, and rollback; able to lead ambiguous work and communicate clearly.

Nice to have - Experience with MCP servers, agent platforms, reusable tool frameworks, or evaluation harnesses and monitoring for LLM systems. - Background in internal tools, solutions engineering, professional services, startups, or founding teams.

Benefits and work setup - Remote-first work setup with flexible paid time off, home office support, and access to shared workspaces. - Medical, dental, and vision coverage, plus mental and physical wellness programs.