Your PropTech product needs more than code. It needs an engineer who understands the business behind each technical request and connects work across your systems.
ORIL embeds an AI-enabled Forward Deployed Engineer (FDE) in your product and technical team for the long term. Your FDE learns your architecture, integrations, and workflows, then turns changing priorities into working solutions.
As your product evolves, so do your engineering needs, and they rarely stay inside one area:
These needs often overlap across product, data, integration, and operational workflows, so every change affects the wider product. When that context is split across teams, repeated handoffs, incomplete requirements, and disconnected technical decisions slow delivery and make it harder to adapt as priorities change.
An ORIL Forward Deployed Engineer works closely with your team over the long term to understand your product and turn evolving needs into practical solutions. Your FDE can support a wide range of engineering needs:
AI-assisted engineering helps your FDE work more efficiently across these areas, while long-term product context ensures continuity. Architecture decisions, integration behavior, product rules, and open issues are documented and shared as part of the engagement, so knowledge doesn’t depend on one person.
A forward deployed engineer learns how your product works, why your workflows matter, and how your technical decisions connect to business priorities.
Build familiarity with your codebase, architecture, data, integrations, current constraints, and operational workflows.
Collaborate with your product, business, and technical stakeholders to clarify requirements, understand needs, evaluate technical options, and align on priorities.
Build and deliver the changes your team has agreed on, from new functionality to updates in existing systems, integrations, and code.
Review and test the work. Release and adoption activities are included where they are part of the agreed scope.
Use feedback to guide further work as your product and business evolve.
The engineer works with access to your codebase, environments, and documentation, communicates regularly with your stakeholders, and coordinates releases with your team.
AI tools support codebase analysis, coding, debugging, test generation, and documentation, and every result is reviewed through the same engineering practices as any other work.
Let’s see if an FDE fits your team.
For real estate and PropTech teams, forward deployed engineering supports three things: product progress, engineering focus, and day-to-day operations.
years building custom software
products delivered
across property management, construction, data, and AI
MLS and IDX integration, listing data, search, lead routing, and third-party integrations.
Applications, screening, lease signing, and rent collection.
Multi-tenant architecture, feature delivery, and scaling.
Portfolio data, underwriting, and investor reporting.
Tenant, lease, maintenance, and payment workflows.
Schedules, field data, documents, and multi-party workflows.
Consumption data, HVAC optimization, and ESG reporting.
Data pipelines, enrichment, data quality, and dashboards.
Device data, building systems integration, and real-time monitoring.
Brickeye serve the construction industry by providing IoT technologies to help construction improve their productivity, reduce the risk…
gReenvision is a platform that enables individuals to envision a future without carbon dioxide emissions…
Have an existing product with evolving engineering needs? Tell us about it, and we’ll discuss whether forward deployed engineering is the right fit before anything is scoped.
27 Jul, 2026 · 10 min read
29 Oct, 2026 · 8 min read
Forward deployed engineering is a service model in which an engineer works embedded with your product and technical team over the long term, learns the business context behind each request, and implements solutions hands-on. At ORIL, it combines AI-enabled engineering with real estate and PropTech expertise and support from ORIL’s QA, DevOps, and design specialists.
A forward deployed engineer is a software engineer who works closely with a client’s product and technical teams to understand a specific product and its constraints, solve technical problems, and implement solutions hands-on. At ORIL, the model combines AI-enabled engineering with long-term product involvement.
A forward deployed engineer solves evolving, product-specific problems with sustained context, while a dedicated developer adds capacity within one role and a dedicated team provides multiple roles for larger initiatives. The models overlap, so the right choice depends on your situation; for larger multi-specialist initiatives, explore our Dedicated Teams service.
Forward Deployed Engineer: Best for an existing product with changing, cross-functional needs. One engineer keeps the full product context and covers product work, integrations and data, AI and automation, and maintenance.
Dedicated Developer: Best for a steady backlog in one area. The developer adds capacity within a defined role and works on tasks inside that role.
Dedicated Team: Best for larger initiatives that need several specialists. The team adds capacity across multiple roles at once.
It fits best when you have a live product whose needs cross product, data, and integration boundaries, and you benefit from one engineer who retains the full context. For a new build that needs multiple roles from day one, Dedicated Teams is the better fit; for a standalone AI initiative, see AI Enablement & Development.
A solutions engineer typically works before a project starts, demonstrating how a product can meet a customer’s needs. A forward deployed engineer implements and maintains working solutions inside your product over the long term.
No. AI-assisted engineering and AI product development are separate. AI tools may support suitable engineering tasks such as research, coding, testing, and documentation, with engineering review and validation. Building AI features into your product is an optional scope decision. For dedicated AI initiatives, see AI Enablement & Development.
Your product and technical leaders retain control of priorities and key decisions. The engineer helps clarify requirements, identify dependencies, evaluate technical options, and implement agreed work. Success criteria and changing priorities are discussed and aligned with your team throughout the engagement.
A typical engagement includes initial discovery, access to the relevant technical environment, collaboration with stakeholders, task prioritization, implementation, review, and ongoing involvement. It can start with one technical challenge and grow into ongoing engineering collaboration as further needs emerge.
Success criteria are agreed for the specific problem. In PropTech products, typical measures include time to deliver a new integration, data accuracy across connected systems, less manual operational work, and fewer recurring technical issues. Metrics are agreed for each engagement and are not guaranteed in advance.
Working with an existing product is the core use case, and it has practical requirements: access to the relevant code and environments, available documentation, an understanding of the architecture, integration constraints, security requirements, and your code review and release practices. We assess these early. Compatibility with every legacy system isn’t automatic.
The engineer coordinates with ORIL’s QA, DevOps, design, or other specialists when a task needs additional expertise, and remains your consistent technical contact where appropriate. Specialist participation depends on the task and agreed scope.
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