Engineering Director, GenAI Solutions

🕒 Janeiro 16

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Placer.ai

SiteLinkedInTodas as Vagas

501 - 1000 funcionários

Fundada em 2016

🏠 Imobiliário

🛒 Varejo

🏢 Corporativo

Real Estate • Retail • Enterprise

Placer. ai é uma empresa de location analytics que fornece a empresas insights sobre o fluxo de pessoas e o comportamento do consumidor com base em dados de localização do mundo físico. Sua plataforma utiliza informações de localização para ajudar os setores de varejo, mercado imobiliário e planejamento urbano a tomar decisões embasadas. A empresa alavanca big data e analytics avançados para transformar dados de localização em inteligência acionável, impulsionando melhorias na eficácia de marketing, seleção de ponto e eficiência operacional.

Descrição

• Lead the technical vision and architecture decisions for our GenAI products, ensuring scalability and performance of the AI-powered location intelligence system. • Establish technical roadmaps aligned with business objectives and scalability requirements. • Design and implement end-to-end AI systems from prototype to production, including LLM integration, agentic architectures, and RAG implementations. • Build robust data pipelines and infrastructure supporting AI/ML workloads at scale. • Oversee model deployment, fine-tuning, and optimization for production environments. • Architect scalable microservices and cloud-native solutions supporting real-time AI applications. • Ensure responsible AI practices including guardrails, performance monitoring, and ethical considerations.

🎯 Requisitos

• Bachelor's degree or higher in Computer Science, Engineering, or a related field. • 10+ years of experience in software development, with 1+ years building production GenAI solutions in B2B SaaS environments. • Expert-level proficiency in backend engineering with Python, Java, Go, or Node.js; proven experience designing microservices architectures and deploying on cloud platforms (AWS, GCP, or Azure). Strong understanding of modern frontend technologies (React/Next.js, TypeScript) and experience architecting full-stack applications with real-time data streaming and WebSocket integrations. • Hands-on experience building and deploying LLM-powered applications using frameworks such as LangChain, LlamaIndex, and APIs from OpenAI, Anthropic, or open-source models. • Experience implementing agentic AI architectures with tool calling, memory systems, and multi-step reasoning capabilities for complex business workflows. • Demonstrated expertise in RAG (Retrieval-Augmented Generation) systems, vector databases (Pinecone, Weaviate, ChromaDB), and semantic search implementations. • Strong foundation in data engineering: designing and optimizing data pipelines, ETL processes, and data infrastructure to support AI/ML workloads. • Proven track record of taking GenAI models from prototype to production, including fine-tuning LLMs, prompt engineering, and implementing guardrails for responsible AI. • Experience with MLOps practices: model versioning, A/B testing, monitoring model performance, and managing the full ML lifecycle in production environments. • Skilled at translating business requirements into technical solutions and collaborating with cross-functional teams including product managers, data scientists, and stakeholders.

🏖️ Benefícios

• Competitive salary. • Excellent benefits.