BrandCommerce

We've outlined our current engineering process below but as we anticipate our team growing considerably this year we're expect to work with new recruits to iterate on the process to ensure it's efficient, agile and also rewarding (hopefully fun) a team structure and process to work in.

Currently one of our founders is head of product and engineering, overseeing product plan, feature prioritization, scheduled releases and roadmap.

In a nutshell we're obsessed with Continuous Integration and try to ship product as often as possible. All engineers, provided they've passed all the safety tests are encouraged to push code as often as possible.

The team presently work to approved product specifications, including any frontend/UI components as wireframes and/or completed designs (output from Sketch and managed in Zeplin).

Engineering sprints are two week cycles with an agreed set of features for each sprint, fixed QA process before internal acceptance testing with product and business teams. If any newly released feature was informed by a specific customer request the feature is deployed to a UAT environment for customer approval prior to platform integration.

At present engineering works in a single team across microservices, ETL, API and UI requirements but as the team grows this year we expect this to be separated into 4 core teams: 1) Microservices Architecture 2) Backend ETL and Vendor Integrations 3) Frontend, UI and client API Integrations 4) Maintenance Engineering Support

Platform integration and deployment is an automated procedure. Right now we're in a highly active cycle so shipping code on a daily basis and we'll continue to do this for our internal roadmap but for customer requests we'll be aiming to limit public releases to a fixed schedule (to be agreed with the team) so that we can consolidate small feature requests and allow all engineers to focus on the good stuff.

We're building a virtual warehouse of available inventory from local retailers across the country.

That might sound simple but challenges to overcome are include: * High volume/frequency ETL enquiry and analysis for inventory checks. * Rapid search and index of high quality of product variants - large scale, real-time complex term search across multiple 3rd party systems. * The resulting caching systems necessary to ensure we don't hose our infrastructure.

Things we're thinking about at the moment: * Building a smarter integration solution to large quantities of 3rd party data repositories (retailer systems) * Pattern learning on product sales for predictive analysis of inventory need based on specific rules and contextual criteria. * Point-to-point logistics intelligence between retailers and customer locations factoring traffic and weather conditions.

Things we're intent on solving: * Explore hardware/software solutions to extracting inventor information from legacy retailer systems (think FoxPro or older and completely offline). * A universal translation layer for ETL between product inventory systems that is easy enough for non-technical content managers to use.