前线部署数据解决方案工程师
Forward Deployed Data Solution Engineer
关于Accelerant
Accelerant 是一个以数据驱动的风险交易所,连接特种保险风险的承保人与风险资本提供者。Accelerant 由一群长期在保险行业工作的高管和技术专家于 2018 年创立,他们有一个共同愿景:重新构建风险交换的方式,使其对每个人都能更高效地运作。Accelerant 风险交易所业务覆盖超过 20 个不同国家和 250 种特种产品,我们自豪的是,我们的保险公司获得了 AM Best A-(优秀)评级。如需更多信息,请访问 。
关于该职位
这不是一个传统的企业架构职位。
Accelerant 正处于快速变化的时期。财务、运营和数据方面的内部系统正在大规模实施。组织内各业务用户正在以超出中央工程团队审查和管理能力的速度构建 AI 赋能的能力。软件的设计和构建方式本身也在发生变化,AI 辅助开发和代理工具正成为日常实践的一部分。
前向部署解决方案工程师的职责是实时响应这一切,从执行工作的团队内部出发,而不是从远处。
该职位人员将嵌入交付项目和产品团队中。他们在决策和代码被创建时进行审查,而不是事后。他们能够快速推动解决方案,独立做出技术判断,并保持质量标准,而不会成为瓶颈。他们是业务需要构建的内容与实际可规模化运营和维护内容之间的桥梁。
你将负责的工作
全程参与工作
你将在合作期间始终坐在交付团队内部,而不是在一旁。你将参加设计和开发会议,审查正在做出的技术决策,并在事情走向错误方向时及时介入。你不会等待评审节点。你就是现场的工程严谨性。
持续验证和指导
你将持续评估所构建的内容是否符合 Accelerant 的架构原则、数据标准和集成模式。如果不符合,你会提出更好的路径并帮助团队实现。当没有现成的文档模式时,你会创建它们。你不会依赖他人在事后制定标准。
快速做出决策
你能够迅速做出合理的技术决策
查看英文原文
About Accelerant
Accelerant is a data-driven risk exchange connecting underwriters of specialty insurance risk with risk capital providers. Accelerant was founded in 2018 by a group of longtime insurance industry executives and technology experts who shared a vision of rebuilding the way risk is exchanged – so that it works better, for everyone. The Accelerant risk exchange does business across more than 20 different countries and 250 specialty products, and we are proud that our insurers have been awarded an AM Best A- (Excellent) rating. For more information, please visit .
About the Role
This is not a traditional enterprise architecture role.
Accelerant is operating in a period of rapid change. Significant internal systems across finance, operations, and data are being implemented. Business users across the organisation are building AI-enabled capabilities at a pace that exceeds the capacity of central engineering teams to review and govern them. The ways in which software is designed and built are themselves changing, with AI-assisted development and agentic tooling becoming part of everyday practice.
The Forward-Deployed Solution Engineer exists to respond to all of this in real time, from inside the teams doing the work, not from a distance.
This person is embedded with delivery programmes and product teams. They review decisions and code as they are made, not after the fact. They drive solutions quickly, make independent technical judgements, and hold the quality bar without becoming a bottleneck. They are the link between what the business needs to build and what can actually be operated and maintained at enterprise scale.
What You Will Do
Be present in the work
You will sit inside delivery teams for the duration of engagements, not alongside them. You will attend design and development sessions, review technical decisions as they are being made, and intervene when something is heading in the wrong direction. You will not wait for a review gate. You will be the engineering rigour in the room.
Validate and guide continuously
You will continuously assess whether what is being built conforms to Accelerant's architecture principles, data standards, and integration patterns. Where it does not, you will propose a better path and help the team take it. Where documented patterns do not yet exist, you will create them. You will not rely on others to produce the standard after the fact.
Take decisions quickly
You will be capable of making a sound technical decision on the day, with the information available, and moving forward. You will not wait for consensus where it is not needed. You will know when to escalate and when to act. The teams you work with will rely on your judgement.
Bridge business-built capability to production
Across Accelerant, business users are building capabilities using AI tools, low-code platforms, and scripting environments. Many of these capabilities are genuinely useful and represent Accelerant's direction of travel. Your job is to assess what has been built, understand what it actually does, identify the gaps between its current state and enterprise readiness, and create a clear path to production. You will ensure these solutions have appropriate data contracts, operational ownership, documentation, and supportability before they are relied upon by the business.
Own integration design
You will design and validate integration patterns between the enterprise systems Accelerant operates, including ERP, CRM, HR, and reinsurance platforms, and the data platform and applications that consume data from them. You will ensure that integrations are clean, well-documented, API-first where appropriate, and built to a standard that does not require the original designer to be present in order to be supported.
Drive data product quality and governance
You will work with delivery teams and the Data Office to ensure that data products are described at source, that ownership is clearly assigned, and that the canonical data models Accelerant depends on are accurate and accessible. You will understand the difference between a physical implementation and a logical data model, and you will be able to articulate why that distinction matters to the people building on top of these products.
Make knowledge durable
You will ensure that technical decisions are recorded, that architectural decision records exist and are accessible, and that the knowledge required to support what Accelerant builds does not live only in individuals. When you leave an engagement, the next person should be able to understand what was decided, why, and what the constraints were.
What You Will Not Do
You will not write lengthy architecture documents that no one reads. You will not operate as a governance gate that slows delivery without adding value. You will not wait for others to bring problems to you. You will not review things in isolation from the teams building them. You will not produce opinions without evidence.
Skills and Experience
Technical foundation
You have strong practical knowledge of cloud platforms, particularly Azure, AWS, and understand how enterprise applications are integrated, operated, and maintained at scale. You are comfortable with API design and integration patterns, including REST, event-driven architectures, and MCP-style tool connectivity. You understand data product concepts, lineage, ownership, and what it means to describe data at source. You can read and review code written by others and provide substantive feedback on it.
AI and modern development practice
You understand how AI-assisted and agentic development approaches are changing how software is built. You have practical experience with at least one AI development framework and understand the governance considerations that apply when AI-generated or AI-assisted capabilities are moved into production. You have a view on what makes an AI-enabled capability enterprise-ready and can assess a prototype against that standard.
Domain awareness
You have experience working with enterprise SaaS platforms, particularly in the finance, operations, or insurance domains. You understand how systems like ERP and CRM platforms model their data, why direct integration to application databases creates problems, and what a canonical data model is trying to solve. Experience with D365, Salesforce, or similar platforms is relevant.
Communication and delivery
You can communicate clearly with both engineers and business stakeholders, and you adjust your register accordingly. You can explain a technical constraint to a non-technical audience without losing accuracy. You can challenge a technical decision in a room without making it personal. You are oriented toward delivery and you hold yourself accountable for whether things actually get done.
Ways of working
You are comfortable with ambiguity. You can engage with a problem that is not fully defined and make progress on it. You do not need complete information before forming a view. You are direct. You document your thinking. You are willing to be challenged and you welcome it.
What Good Looks Like
After six months in this role, the following should be true.
Delivery programmes you have been embedded with are running with fewer design-level surprises after build starts. Integration patterns you have reviewed or created are being used by other teams as a starting point rather than each team solving the same problems independently. Business-built capabilities that have come through your assessment have a clear production status, documented ownership, and a supportability record. Technical decisions made during your engagements are findable on Confluence and have enough context that someone new to the programme can understand them. The teams you have worked with ask for you to be involved earlier in their next piece of work, not later.
Originally posted on Himalayas