Forward Deployed Data Solution Engineer

Accelerant; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Accelerant embeds Forward-Deployed Solution Engineers inside delivery programmes, reviewing decisions and code in real time to ensure architectural rigor and governance. The role acts as the link between business needs and scalable enterprise operations, focusing on rapid yet responsible delivery.

You will guide integration with ERP/CRM platforms, data contracts, and documentation while balancing speed with long-term maintainability across finance, operations, and data domains.

Qualifications

• Technical foundation with cloud platforms and enterprise integration experience.
• Experience with AI-assisted and agentic development approaches and governance considerations.
• Domain awareness of enterprise SaaS, ERP, and CRM data models.
• Clear communication with engineers and business stakeholders; delivery-oriented.

Responsibilities

• Embed with delivery teams and attend design sessions, providing engineering rigour in real time.
• Assess conformance to architecture principles, data standards, and integration patterns; create patterns where none exist.
• Make on-the-day technical decisions with available information and move forward without unnecessary delays.
• Bridge business-built capabilities to production with proper data contracts and ownership.
• Own integration design across ERP, CRM, HR, and data platforms, API-first where appropriate.
• Drive data product quality, governance, and accurate canonical data models.
• Capture decisions and maintain accessible architecture documents for continuity.

Skills

Azure

AWS

API design

Integration patterns

Data lineage

Canonical data model

AI development

Domain knowledge

Stakeholder communication

Tools

Confluence

Salesforce

Dynamics 365

Job description

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 escape 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.