Lead Automations Analyst

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Automations Analyst based in United States.

• 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.

• 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.

• 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, col