高级数据平台工程师
Defcon Senior Data Platform Engineer
关于 DEFCON AI
在面对颠覆时的韧性。DEFCON AI 是一家洞察公司,利用人工智能、数学优化、数据分析和软件工程,对复杂系统进行弹性优化。在当今不断变化的世界中,DEFCON AI 的技术使结果与运营目标保持一致,提升决策质量,并赋能客户预测、评估和减轻颠覆的影响。
如果你的答案是“当两条记录不一致时,从不覆盖”,那么这个职位就是为你而设的。
职位简介
作为高级数据平台工程师,你将负责平台上每个已解决实体的持久化视图:存储层保存我们所知道的内容、每个事实的来源、我们对其的信心程度,以及该画面随时间的变化。当两个来源不一致时,两者都会保留并附有证据。当有人询问某一天我们相信什么,以及原因时,平台可以给出答案。
你将加入分析和 AI 工程团队,该团队构建了一个系统,从数十个不同的来源获取记录,将其解析到正确的实体,突出分析师应优先审查的内容,并提供透明、可解释的推荐,用户可以信任这些推荐。在安全的政府云环境中运行,该平台依赖于一个存储层,不会悄悄地抹去来源之间的不一致。
上游匹配是概率性的。一次匹配会带有置信度分数,而不是简单的“是”或“否”,存储层会保留这种不确定性,而不是将其合并为一条干净的记录。来源会毫无预警地改变形态,也没有共享的键可供连接,因此这是一个当前的数据工程问题,而不是经典的仓储问题。
这个职位所需的资历是关于判断力,而不是工具的广度:知道为什么从不覆盖,以及一年后能够用证据重新构建过去的决定。如果你的直觉是当记录不一致时保留两者并让人类决定,那么你会在这里感到自在。
这是一个完全远程的职位,根据需要偶尔前往 DEFCON AI 总部、客户现场和合作伙伴设施。
主要职责
· 设计并构建存储层,以保留来源不一致和历史记录,而不是在写入时解决它们
· 构建第一个版本的结果和证据存储:按人保存的结果与原始记录相关联,先前结果和人工反馈分别保留,以及置信度
查看英文原文
ABOUT DEFCON AI
RESILIENCE IN THE FACE OF DISRUPTION. DEFCON AI is an insights company that leverages artificial intelligence, mathematical optimization, data analytics, and software engineering for resilient optimization of complex systems.
In today’s dynamically changing world, DEFCON AI’s technology aligns outcomes with operational goals, better decision making, and empowers customers to anticipate assess, and mitigate the impacts of disruptions.
If your answer to “the two records disagree” is never overwrite, this role was built for you.
About the Role
As a Senior Data Platform Engineer, you’ll own the durable view of every resolved entity on the platform: the storage layer that holds what we know, where each fact came from, how confident we are in it, and how that picture has changed over time. When two sources disagree, both are kept with their evidence. When someone asks what we believed on a given date, and why, the platform can answer.
You’ll join the analytics and AI engineering team behind a system that ingests records from dozens of disparate sources, resolves them to the right entity, highlights what analysts should review first, and provides transparent, explainable recommendations that users can trust. Operating within a secure government cloud environment, the platform depends on a storage layer that never quietly erases a disagreement between sources.
Upstream matching is probabilistic. A match arrives with a confidence score rather than a yes, and the storage layer carries that uncertainty forward rather than collapsing it into one clean record. Sources change shape without warning and there is no shared key to join on, so this is a current data-engineering problem rather than a classic warehousing one.
The seniority this role calls for is about judgment, not tooling breadth: knowing why you never overwrite, and being able to reconstruct a past decision with its evidence a year later. If your instinct when records disagree is to preserve both and let a human decide, you’ll be at home here.
This is a fully remote role with occasional travel to DEFCON AI headquarters, customer sites, and partner facilities as needed.
Key Responsibilities
· Design and build the storage layer that preserves source disagreement and history rather than resolving them away at write time
· Build the first release’s result and evidence store: saved per-person results linked to the originating record, prior results and human feedback retained separately, and configuration versions on every result
· Implement provenance and lineage across every node and edge against the platform’s evidence-record contract
· Store the versioned rule library and configuration, and record on every result the exact rule versions and ordered context supplied to any model-assisted step
· Ensure every write is traceable to its origin and every decision is reproducible
· Carry match confidence and other uncertainty forward through the platform rather than collapsing it into a single value
· Support point-in-time questions: what did we believe about this entity on this date, and on what evidence
· Define, with entity resolution and ML teammates, what the storage layer needs to receive and what it must serve downstream
Required Qualifications
· 6+ years in data engineering or data platform engineering, including production experience with versioned, temporal, or historized data models
· Experience designing storage where history, provenance, and source disagreement are first-class rather than resolved away
· Comfort building on probabilistic upstream output rather than a clean shared key
· Strong Python and SQL, with production experience on PostgreSQL or comparable
· US Citizenship Required
· Active US Secret clearance
Preferred Qualifications
· Experience building the storage layer downstream of an entity-resolution or record-linkage system
· Bi-temporal, event-sourced, graph, or temporal data modeling in production
· Federal, government, or regulated-industry experience where a historical decision had to be reproducible on demand
· Active Top Secret clearance
What Success Looks Like
· A durable view that never silently overwrites a disagreement between sources
· “What did we believe on this date, and on what evidence” is answerable a year later
· The storage layer holds up as probabilistic match output flows in, rather than assuming a clean join
What We Offer
· A fully remote, results-based environment
· Competitive salary, bonus, and equity package
· 100% employer paid, comprehensive health insurance including medical, dental, and vision for you and your family
· Unlimited PTO, with your manager’s approval
· Flexible work environment where you manage your work day
· 14 weeks of fully-paid parental leave
Salary Range: $165,000—$200,000. This represents the typical salary range for this position based on experience, skills, and other factors.
We’re an Equal Opportunity Employer: You’ll receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.
Applicant Data Disclosure
By submitting an application, you acknowledge that Defcon AI uses third-party service providers to facilitate its recruitment and hiring processes. These providers include applicant tracking systems, candidate verification platforms, and fraud detection tools (collectively, "Hiring Platforms"). Your application materials, including your résumé, cover letter, work samples, responses to application questions, and any other information you submit, may be transmitted to and processed by these Hiring Platforms for the following purposes:
- Managing and administering your application throughout the hiring process;
- Verifying the accuracy and authenticity of application materials, including by cross-referencing information you provide against publicly available sources and proprietary databases;
- Identifying indicators of potentially fraudulent, fabricated, or materially misleading application content, including but not limited to discrepancies between submitted materials and publicly available professional profiles, geographic anomalies, and fabricated work histories.
Applications that are flagged through this process as containing indicators of fraud or material misrepresentation may be declined from further consideration. If you have questions about the status of your application or the evaluation process, please .
Defcon AI requires its Hiring Platform providers to process your information solely for the purposes described above and in accordance with applicable law. Your information will be retained only for as long as necessary to fulfill these purposes and any applicable legal obligations, after which it will be deleted in accordance with Defcon AI's data retention policies.
For more information about how your data is used, please refer to our Privacy Policy andApplicant Privacy Notice.
Originally posted on Himalayas