Senior Data & AI Engineer
位置：远程 （美国）工作类型：兼职合同，初步三个月的参与部门：产品和技术报告到：产品负责人####关于 NeoReach NeoReach 是一家创作者技术公司和影响力营销领导者，被财富500强大品牌，全球企业和颠覆性初创公司信任，以提供推动文化发展和推动商业成果的运动。我们将代理专业知识与专有创作者数据基础设施，性能工具和人工智能启用的工作流程结合起来。我们的生态系统包括 Influencers.com,帮助创作者增长他们的业务并开放新的机会的平台。我们正在寻找一个经验丰富的工程师来加强我们的数据基础设施，并建立实用的人工智能驱动工具.####*角色概述高级数据和 AI 工程师将连接业务系统，提高数据质量，开发可靠的工具，帮助团队有效工作和做出更好的决定。这是个人的贡献者作用，从发现到部署的工作。你将直接与产品领导合作，并与工程和商业团队合作，以提供具有可测量的解决方案。初步参与将优先考虑定义的数据集成和人工智能启用的工作流程，在开端确定范围和里程碑。#####关键责任数据基础设施和集成 - 评估现有数据源和工作流程以确定缺口和机会 - 建立连接 API,数据库和商业应用程序的集成 - 将记录标准化，解决重复件并制定一致的数据定义 - 实施验证，监控和处理错误的人工智能工具和自动化 - 构建研究，信息检索，分析和反复的工作流程的工具 - 与批准的内部系统和数据连接人工智能应用程序 - 使用人工智能编码工具来加速开发，同时保持质量和可靠性 - 通过适当的访问控制和人力审查，评估准确性，有用性和成本。产品开发与交付-将业务要求转化为现实的技术里程碑- 发出原型，纳入用户反并部署成功工具到生产中- 沟通进展，妥协和阻碍者-采取措施，节省时间和运营改进文件和知识传输- 维护公司所有代码，建筑文档和部署说明 - 合作
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Location: Remote (U.S.)
Employment Type: Part-Time Contract, Initial Three-Month Engagement
Department: Product & Technology
Reports To: Head of Product
#### About NeoReach
NeoReach is a creator-technology company and influencer marketing leader trusted by Fortune 500 brands, global enterprises, and disruptive startups to deliver campaigns that move culture and drive business outcomes.
We combine agency expertise with proprietary creator-data infrastructure, performance tools, and AI-enabled workflows. Our ecosystem includes Influencers.com, a platform helping creators grow their businesses and unlock new opportunities.
We’re seeking an experienced engineer to strengthen our data infrastructure and build practical AI-powered tools.
#### Role Overview
The Senior Data & AI Engineer will connect business systems, improve data quality, and develop reliable tools that help teams work efficiently and make better decisions.
This is a hands-on individual contributor role, owning work from discovery through deployment. You will work directly with product leadership and collaborate with engineering and business teams to deliver focused solutions with measurable impact.
The initial engagement will prioritize a defined data integration and an AI-enabled workflow, with scope and milestones established at kickoff.
#### Key Responsibilities
Data Infrastructure and Integrations
- Assess existing data sources and workflows to identify gaps and opportunities
- Build integrations connecting APIs, databases, and business applications
- Standardize records, resolve duplicates, and establish consistent data definitions
- Implement validation, monitoring, and error handling
AI Tools and Automation
- Build tools for research, information retrieval, analysis, and recurring workflows
- Connect AI applications to approved internal systems and data
- Use AI coding tools to accelerate development while maintaining quality and reliability
- Evaluate accuracy, usefulness, and cost, with appropriate access controls and human review
Product Development and Delivery
- Translate business requirements into realistic technical milestones
- Ship prototypes, incorporate user feedback, and deploy successful tools into production
- Communicate progress, tradeoffs, and blockers
- Measure adoption, time savings, and operational improvements
Documentation and Knowledge Transfer
- Maintain company-owned code, architecture documentation, and deployment instructions
- Collaborate with engineering on security, maintenance, and system ownership
- Ensure internal teams can operate and extend delivered solutions