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Remote role and mid-level (3+ years) attract candidates, but specialized LLM production skills moderate competition.
Core AI engineering skills are transferable, but RevOps and CRM integration requirements add moderate domain specificity.
Explicit 3+ years plus mandatory production LLM, RAG, evaluation, and governance skills increase shortlisting rigidity.
Design, build, deploy, and operate AI-powered workflows, agents, and automations integrated within core revenue operations systems such as Salesforce, Microsoft 365, and Azure AI.
Develop and maintain LLM evaluation frameworks, measurement metrics, and telemetry that connect AI system usage to operational and revenue outcomes.
Implement hallucination-reduction techniques and ensure AI systems are production-ready, reliable, secure, and aligned with measurable business impact.
Minimum 3 years of experience in AI engineering or related fields involving deployment of AI or automation systems in production.
Strong hands-on experience with LLM-based systems including prompt engineering, retrieval-augmented generation (RAG), and orchestration.
Experience with RevOps systems (e.g., CRM, GTM tools) and building production AI workflows.
Work Experience Required: Minimum 3 years as explicitly mentioned in the JD.
Experienced in operating production-grade AI/automation systems focused on reliability, evaluation, and measurable business outcomes rather than experimentation.
Comfortable translating complex AI product requirements into scalable, maintainable, and governed implementations in cross-functional environments.
Strong analytical and debugging skills related to AI system behavior with the ability to communicate insights to technical and non-technical stakeholders.