Senior CX Platform Engineer

<h3>Accountabilities</h3><li>Build and operate production-grade agentic applications and multi-step AI workflows for account research, success planning, status reporting, customer onboarding, and related customer experience processes.</li><li>Develop and maintain MCP servers and secure connectors for enterprise platforms and data sources, including CRM, customer success, professional services, learning, communications, and data warehouse systems.</li><li>Use coding agents and AI-assisted development tools as part of the daily engineering workflow for planning, implementation, refactoring, testing, code review, and documentation while maintaining ownership of production quality.</li><li>Build and evolve the team's agent development harness, including shared conventions, reusable skills, commands, hooks, subagents, and continuous integration checks.</li><li>Establish evaluations, tracing, observability, and human-in-the-loop controls to make AI systems measurable, auditable, secure, and reliable when handling customer and business data.</li><li>Develop and maintain the application platform, including AWS infrastructure, gateway capabilities, Terraform configuration, deployment processes, and core applications and integrations.</li><li>Deliver production-quality Python and TypeScript applications with robust testing, CI/CD, monitoring, security controls, documentation, and operational runbooks.</li><li>Design applications and platform components for maintainability and handoff, emphasizing shared ownership and reducing reliance on individual engineers.</li><li>Partner directly with Customer Success, Digital Success, Professional Services, Education Services, and Training teams to prototype solutions rapidly and bring valuable applications into production.</li><li>Translate field and stakeholder feedback into reusable technical patterns, reference implementations, development paths, and enablement materials.</li><li>Contribute to platform and product improvements, provide feedback to Product and Engineering teams, and participate in upstream or open-source contributions where appropriate.</li><li>Mentor engineers and non-engineering stakeholders on agentic development practices while raising the team's standards for architecture, testing, security, and code review.</li><h2>Requirements</h2><li>Demonstrated experience building and operating production software, including ownership of substantial projects from ambiguous requirements through deployment and ongoing operation.</li><li>Hands-on professional experience using coding agents such as Claude Code, Cursor, Codex, GitLab Duo, or comparable AI development tools in production engineering workflows.</li><li>Practical experience building with large language models beyond conversational interfaces, including tool use, MCP servers, agent loops, retrieval and context design, prompt engineering, workflow orchestration, and AI evaluations.</li><li>Strong Python development skills with FastAPI, Flask, or comparable frameworks, alongside TypeScript experience with Vue, React, or similar frontend technologies.</li><li>Experience designing APIs, authentication and authorization mechanisms, and secure systems for handling customer and business data.</li><li>Hands-on experience with AWS services such as ECS, RDS, and Lambda, as well as Terraform, Docker, and applications operating behind SSO platforms such as Okta.</li><li>Experience integrating enterprise systems through REST and GraphQL APIs.</li><li>Strong understanding of Git-based development workflows, merge requests, automated testing, and CI/CD practices.</li><li>Ability to translate complex workflows from non-engineering stakeholders into clear technical plans and scalable platform solutions.</li><li>Strong asynchronous communication skills, including experience writing design documents, architecture decisions, technical documentation, and enablement materials.</li><li>Ability to balance rapid experimentation with production reliability, security, observability, maintainability, and long-term ownership.</li><li>Experience with agent harness customization, enterprise AI governance, data controls, customer success or professional services platforms, or learning technologies is an advantage.</li><li>Familiarity with platforms such as Salesforce, Gainsight, Kantata, Thought Industries, Snowflake, or comparable enterprise systems is a plus.</li><li>Technical writing, public speaking, open-source contributions, or demonstrated thought leadership in agentic AI development are valued.</li><h2>Benefits</h2><li>Remote work environment for eligible employees in the United States.</li><li>Base salary range of<strong>$139,200–$235,200 USD</strong>, depending on level, experience, skills, knowledge, abilities, equity considerations, and geographic location.</li><li>Equity compensation and employee stock purchase plan.</li><li>Flexible paid time off.</li><li>Parental leave and wellness-focused support.</li><li>Growth and development funding to support ongoing professional learning and career growth.</li><li>Team member resource groups and an inclusive, collaborative work environment.</li><li>Opportunities to work on production AI systems with meaningful operational impact.</li><li>Exposure to modern AI development practices, enterprise platforms, cloud infrastructure, and agentic technologies.</li><li>Opportunity to collaborate with distributed teams across Customer Success, Professional Services, Education Services, Training, Product, and Engineering.</li>