Principal AI Engineer

🕒 Agosto 7

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🔴 Especialista

🤖 Engenheiro de IA

👻 Score fantasma 29%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

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BuzzBoard

SiteLinkedInTodas as Vagas

51 - 200 funcionários

💼 Consultoria

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

BuzzBoard descobre insights baseados em dados sobre pequenas e médias empresas que promovem conversas mais significativas para profissionais de marketing e vendedores, resultando em aumento de vendas ao longo do ciclo de vida do cliente. Ao aplicar ciência de dados e sinais digitais à mais extensa coleção mundial de inteligência sobre PMEs, BuzzBoard responde à pergunta mais importante para profissionais de marketing e vendedores: por que meus prospects e clientes desejariam se envolver? BuzzBoard transforma interações de vendas improdutivas em oportunidades personalizadas para melhorar o engajamento do cliente, agendar mais reuniões e fechar negócios mais rapidamente.

Descrição

• Design AI systems behind content generation, business intelligence, recommendations, and agentic workflows • Create reusable prompts, evaluation flows, orchestration layers, and architecture patterns across products • Lead agent design covering reasoning, tool/API calls, state management, checkpointing, handoffs, and safe failure • Design end-to-end RAG pipelines, including chunking, embeddings, metadata, reranking, and retrieval evaluation • Own model selection based on cost, latency, accuracy, and reliability, including fallback and model-switching behavior • Build evaluation frameworks and regression testing for output quality, edit ratio, hallucination rate, schema adherence, latency, failure rate, and inference cost • Partner with engineering and platform teams on deployable, observable, and maintainable systems • Package services with Python, FastAPI/Flask, and Docker when appropriate • Diagnose AI-specific production issues such as rate limits, cost spikes, model failures, and degraded output • Mentor GenAI engineers and review designs, prompts, workflows, and evaluations • Translate product requirements into architecture with measurable acceptance criteria • Communicate technical tradeoffs to engineers and leadership

🎯 Requisitos

• 5+ years in engineering, AI, ML, or data-product work • 3+ years of hands-on GenAI/LLM systems experience • Production GenAI experience with systems carrying real traffic • Deep working knowledge of LLMs and SLMs, prompt engineering, structured outputs, and tool/function calling • Hands-on experience with at least two major LLM ecosystems • Experience building production RAG with vector stores such as Chroma, Pinecone, Weaviate, or FAISS; embeddings, semantic search, and measured retrieval quality • Hands-on experience with at least one agentic framework such as LangGraph, CrewAI, AutoGen, or Semantic Kernel • Understanding of agent memory, state, tool integration, and failure handling • Strong Python skills • Comfort with REST APIs, Docker, a cloud platform, and basic CI/CD • Demonstrated evaluation work including regression testing, hallucination checks, schema validation, and output scoring • Ability to define metrics for quality, reliability, cost, and business impact • Track record guiding a small team or owning AI architecture end to end • Ability to create structure in a fast-moving environment with shifting requirements • Preferred: fine-tuning or supervised training workflows • Preferred: SLM and open-source model deployment using vLLM, Ollama, or TensorRT-LLM • Preferred: multimodal work across text, image, audio, or video • Preferred: Kubernetes or serverless deployment • Preferred: evaluation/observability tooling such as LangSmith, MLflow, or Weights & Biases • Preferred: marketing technology, SMB intelligence, or content-automation experience • Preferred: responsible AI, privacy, security, and compliance practice • Preferred: experience scaling high-volume AI systems

🏖️ Benefícios

• Fully remote • A production GenAI foundation already carrying real volume • Genuine architectural ownership over the agentic systems that come next • A small, high-context team that moves quickly and argues about the work • Real impact on small businesses