Lead Automations Analyst

Accountabilities

• • Own the end-to-end delivery of AI solutions, translating customer success problems into solution designs, building workflows, defining success criteria, and deploying solutions into production.
  • Design and develop orchestrators, sub-agents, skills, prompts, and knowledge-base components that enable AI-powered workflows.
  • Establish feedback and evaluation mechanisms, including user signals, logs, and quality metrics, to measure solution performance and identify opportunities for improvement.
  • Monitor production AI solutions for quality drift and continuously iterate based on advisor, customer, and evaluation feedback.
  • Design AI workflows across the full customer interaction lifecycle, including pre-call preparation, in-call guidance, post-call grading, summaries, transcription-driven follow-ups, and internal knowledge retrieval.
  • Identify gaps in AI platform capabilities and partner with Revenue Operations and engineering teams to define requirements, acceptance criteria, edge cases, and expected business impact.
  • Participate in technical design reviews, validate new platform capabilities, and integrate them into production solutions once available.
  • Partner with Quality Assurance and Success leadership to prioritize fixes, enhancements, and new AI workflows based on evaluation data, business impact, and customer needs.
  • Establish technical standards and reusable patterns for AI solution design, testing, deployment, observability, model selection, orchestration, and prompt architecture.
  • Create documentation and playbooks that improve consistency, quality, and onboarding across the AI automation function.
  • Stay current with developments in LLM behavior, model releases, orchestration approaches, evaluation techniques, and emerging AI tooling.
  • Conduct experiments with new models and AI techniques and share relevant findings with Success, Quality Assurance, and engineering stakeholders.

  Requirements

  • 7+ years of experience in AI/ML solution development, technical product management, prompt engineering, automation engineering, applied AI, or a closely related field involving end-to-end solution ownership.
  • Strong curiosity and a self-directed learning mindset, with the ability to continuously develop expertise as AI technologies and best practices evolve.
  • Practical understanding of LLM behavior, including prompt design, orchestration patterns, model selection, common failure modes, and evaluation approaches.
  • Strong understanding of databases and how data moves between interconnected systems.
  • Ability to read and understand code sufficiently to troubleshoot integrations, understand systems running within an AI platform, and engage in substantive technical discussions with engineers.
  • Demonstrated ability to scope ambiguous problems, design practical solutions, develop clear requirements and acceptance criteria, and drive delivery through production.
  • Strong written and verbal communication skills, including the ability to translate complex business or customer success problems into clear AI solution designs.
  • Strong end-to-end ownership mindset, with accountability for both delivery and measurable outcomes.
  • Bachelor’s degree in a relevant discipline or equivalent practical experience.
  • Experience with AI development platforms such as Claude, Cursor, or comparable tools is preferred.
  • Experience designing orchestration patterns, sub-agent workflows, or multi-step AI solutions is advantageous.
  • Familiarity with retrieval-augmented generation, vector databases, and knowledge-base architecture is a plus.
  • Experience with SQL or comparable database querying languages is preferred.
  • Familiarity with APIs, webhooks, and data integration workflows is beneficial.
  • Experience in customer success, customer support, sales enablement, or contact-center environments is a plus.
  • Experience deploying AI workflows into production environments and writing technical requirements for engineering teams is highly desirable.
  • Experience with SaaS platforms or customer-facing business applications is advantageous.

  Benefits

  • Opportunity to work on production AI solutions with direct impact on customer and advisor experiences.
  • Senior individual contributor scope with significant ownership and a clear trajectory for professional growth.
  • Exposure to rapidly evolving LLM technologies, AI orchestration, automation, and applied AI workflows.
  • Opportunity to collaborate with cross-functional teams spanning Success, Quality Assurance, Revenue Operations, and engineering.
  • Global, remote-first working environment with an international team.
  • Culture focused on creativity, collaboration, experimentation, continuous learning, and measurable impact.
  • Opportunity to contribute to the development of new AI capabilities and technical standards across the organization.
  • Equal opportunity workplace with employment decisions based on qualifications and business needs.
  • Access to a global community supporting millions of businesses through technology-driven customer engagement and growth.