Lead Automations Analyst
New
J
JobgetherAI Automation
Based in United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 7+ years
- Required Skills
- SQLRESTful APIsPrompt EngineeringLLM
Requirements
- 7+ years of experience in AI/ML solution development, technical product management, prompt engineering, automation engineering, applied AI, or a closely related field.
- 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 to troubleshoot integrations and engage in technical discussions with engineers.
- Demonstrated ability to scope ambiguous problems, design solutions, and drive delivery through production.
- Strong written and verbal communication skills.
- Strong end-to-end ownership mindset with accountability for 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.
- Experience designing orchestration patterns, sub-agent workflows, or multi-step AI solutions.
- Familiarity with retrieval-augmented generation, vector databases, and knowledge-base architecture.
- Experience with SQL or comparable database querying languages.
Responsibilities
- 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, and automated follow-ups.
- Identify gaps in AI platform capabilities and partner with Revenue Operations and engineering teams to define requirements and acceptance criteria.
- Establish technical standards and reusable patterns for AI solution design, testing, deployment, observability, and orchestration.
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