AI Specialist (Applied AI) at BPM LLP | Torre

AI Specialist (Applied AI)

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Full-time

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Remote (for India residents)
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Emma of Torre.ai
14 days ago

Responsibilities


As an AI Specialist at Caravel, you'll design and deliver applied AI solutions for our clients — from LLM-powered workflows and retrieval systems to agentic automation that plugs into the systems businesses actually run on. You'll be client-facing, working US hours from India or South America, and you'll partner with our prompt-development pod to take solutions from design to production. If you like solving real business problems with AI — not building demos — this is your seat.Key Responsibilities:Scope, design, and deliver applied AI solutions — LLM workflows, RAG systems, agentic automation, and model evaluation — integrated into client and business systems.Work directly with clients through discovery, solution design, demos, and delivery, translating business problems into AI that holds up in production.Define patterns and specifications for the prompt-development pod to build against; review and guide their production builds.Establish evaluation criteria and measure solution quality, accuracy, and ROI.Advise clients on AI readiness, data, and responsible, safe deployment.Contribute to Caravel's reusable AI accelerators and go-to-market offerings.Preferred Qualification4+ years in AI/ML, data science, or applied AI engineering, including hands-on work with LLMs in production or near-production settings.Strong Python and modern AI tooling; experience with RAG, embeddings/vector stores, and at least one major LLM provider or framework.Client-facing skills — you can lead a working session, explain trade-offs to non-technical stakeholders, and manage scope.Fluent English and consistent overlap with US business hours.A pragmatic, outcomes-first approach — you optimize for client value, not novelty.Preferred Skills:Consulting or professional-services background.Exposure to ERP/CRM platforms (NetSuite, Salesforce) or finance/operations data.Experience standing up evaluation, observability, or guardrail frameworks.Cloud (AWS/Azure/GCP) and MLOps familiarity.