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BEES

Runs a digital ordering platform for small retailers

Data Product Manager - GenAI & Search

Technical Product ManagementConfirmed live in the last 24 hours
Full-timeSão Paulo, State of São Paulo, Brazil

About the Job

Requirements

  • Strong technical background demonstrated through a degree or prior hands-on experience in Computer Science, Software Engineering, Data Science, or Systems Architecture, sufficient to guide technical discussions and architecture decisions with engineers and scientists.
  • Proven experience managing data, Search, or AI/ML-driven products, with a strong grasp of Generative AI concepts including large language models, retrieval-augmented generation, prompt engineering, agents, and embeddings, as well as information retrieval and search, including lexical versus vector/semantic search, ranking, and indexing.
  • Strong understanding of the AI/ML and Search lifecycle, including data pipelines, indexing, context retrieval, evaluation frameworks, deployment, monitoring, and continuous iteration.
  • Ability to translate ambiguous business problems into clear technical product requirements and architectural specifications.
  • Strong written and verbal communication skills to bridge business, software engineering, and data science audiences.
  • Fluent English to collaborate effectively with global teams.
  • Willingness to work hybrid in São Paulo.

Responsibilities

  • Partner with global commercial and product stakeholders across LATAM, the US, and global markets to enable product understanding, drive adoption, and identify new Generative AI and Search use cases.
  • Educate stakeholders on large language model and Search capabilities, trade-offs including latency, cost, accuracy, and hallucinations, limitations, and the product roadmap.
  • Provide regular updates to internal stakeholders and leadership on product adoption, search relevance, agent performance, and business impact.
  • Own quarterly product planning in close collaboration with AI/ML Engineers, Data Scientists, Data Engineers, and Software Engineers.
  • Balance business value, model and prompt experimentation, search relevance tuning, and platform and infrastructure scalability when defining priorities.
  • Assess team capacity, technical debt, and delivery risk to ensure plans are realistic and aligned with product and business strategy.
  • Partner with technical teams to execute the quarterly backlog and deliver Generative AI and Search capabilities.
  • Drive end-to-end delivery of conversational AI and agentic workflows; semantic and hybrid search engines, including retrieval-augmented generation and vector search; scalable, low-latency APIs; evaluation frameworks, including LLM-as-a-judge and offline and online evaluations; and observability dashboards.
  • Define epics, high-level requirements, and technical specifications, and lead refinement sessions focused on system architecture, user experience, search relevance and ranking, and large language model behavior, guardrails, and performance.
  • Lead Agile ceremonies, including daily stand-ups, sprint planning, reviews, and retrospectives, and act as a technical sounding board for the squad.
  • Track delivery and performance metrics and produce sprint summary reports covering team productivity, Search and AI quality metrics such as NDCG, MRR, faithfulness, latency, and token cost, and usage and adoption trends.
  • Maintain relationships with technical, commercial, and senior leadership stakeholders.
  • Present quarterly roadmaps, architectural trade-offs, and progress updates.
  • Manage expectations by negotiating scope, timelines, and technical trade-offs across internal teams and customers.

Desired Qualifications

  • Advanced Spanish is a plus.
  • A solid background in Technical Product Management or Data Product Management, preferably building AI, Generative AI, or Search platforms and products.
  • Hands-on experience writing epics, high-level requirements, API contracts, and technical documentation.
  • Deep understanding of modern software architecture, including distributed systems, relational and NoSQL databases, vector databases, REST and streaming APIs, and cloud infrastructure.
  • Experience working in Agile environments leading highly cross-functional technical teams spanning Data Science, AI/ML Engineering, MLOps, Backend, and Frontend.

About the Company

BEES

Runs a digital ordering platform for small retailers

BEES runs a business-to-business commerce platform where small and medium-sized retailers order stock from brewer AB InBev and other consumer brands. AB InBev created it to digitize how its brands reach retailers, and other brand owners and distributors use the same system to run their own sales and delivery. Its connected tools cover ordering, payments, delivery management, customer service and data for management teams. Built-in AI recommends products and offers to each retailer and plans sales visits and delivery routes for field teams. BEES first ran in the Dominican Republic before expanding to other countries, and it is headquartered in Rotkreuz, Switzerland.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Risch-Rotkreuz, Switzerland
Founded
2019

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