David Robertson, Director Enterprise Structure – Sofware Engineering | Functions, Exeter Finance
David Robertson, Director Enterprise Structure – Sofware Engineering | Functions, Exeter Finance
In an interview with CIOReview, Mr. David Robertson, Director of Enterprise Structure at Exeter Finance, discusses the challenges and rising traits on this planet of bespoke software program engineering, sharing his insights into successfully navigating them.
David Robertson is the Director of Enterprise Structure at Exeter Finance, the place he leads innovation in cloud-native platforms and automation in bespoke and AI integration. With a powerful give attention to scalability, safety, and effectivity, David makes a speciality of integrating AI, DevOps, and sustainable automation practices. He brings a long time of expertise in driving innovation, enhancing engineering excellence, and aligning expertise technique with enterprise targets to ship measurable, long-term worth.
Present Function & Duties
I function the Director of Enterprise Structure at Exeter Finance, a premier auto finance firm. My staff is answerable for constructing and automating the bespoke methods that run crucial components of our automotive lending enterprise. The methods we assist are tailor-made in-house—designed to fulfill the corporate’s distinctive wants and to evolve as these wants change.
The core focus of my position is figuring out alternatives to boost effectivity, scalability, and resilience. A good portion of our efforts is devoted to decreasing the guide and repetitive points of platform improvement and deployment. By automating these areas, we allow our groups to dedicate extra time to high-value work, together with crucial problem-solving and knowledgeable decision-making that instantly impacts the enterprise. Extra lately, we’re additionally exploring how generative AI can improve our platforms as an embedded functionality that provides worth throughout the methods themselves.
Challenges in Bespoke Improvement
One of many constant challenges in bespoke software program engineering is safety. The problem is especially urgent when organizations aren’t simply integrating third-party instruments however constructing software program from the bottom up. Past assembly purposeful necessities, the software program should be safe and performant by design.
To handle this, we’ve built-in automation into our safety workflows. This helps mitigate dangers with out requiring each staff member to be an knowledgeable in each safety element. Automation acts as a bridge, filling data gaps and implementing consistency, which permits us to remain centered on delivering the options and capabilities the enterprise actually wants.
The Worth of a Studying Mindset
A number of years in the past, my staff and I had been tasked with one thing totally new for the group: constructing a customer-facing utility within the cloud. On the time, this was a big departure from our conventional method, which relied closely on non-public information facilities. We had been ranging from scratch—new structure, new instruments and restricted inner expertise with cloud-native improvement.
The educational curve was steep, however the realization got here rapidly that automation could be the important thing to scaling effectively. We developed tooling to automate infrastructure provisioning, utility deployment and testing processes. This allowed us to streamline the complete improvement lifecycle—from spinning up environments to publishing modifications—with no need to create a number of groups to handle every step manually. By embracing automation early, we will speed up supply and set up a basis for long-term agility and operational effectivity.
Imaginative and prescient for the Future
AI continues to dominate headlines, however the focus is shifting from novelty to sensible utility. Fairly than treating AI as a standalone function, the objective is to embed it as a core functionality or one other instrument within the engineering toolkit used to resolve present enterprise challenges extra successfully. Over the following 12 to 18 months, the main focus will probably be on purposeful integration relatively than experimentation.
There may be additionally a rising array of AI instruments designed to spice up productiveness, comparable to copilots, digital assistants, and clever automation. These can ship significant features, however their effectiveness is dependent upon how effectively they align with present workflows and enterprise aims. Success will come from deploying AI with clear intent and measurable outcomes.
When evaluating AI instruments—whether or not off-the-shelf or custom-built—it’s price contemplating extra than simply options and performance. Governance, threat, and safety ought to be entrance and middle, particularly when working with delicate information like buyer data or proprietary enterprise info. Understanding the place information is saved, the way it’s processed, and the way lengthy it’s retained is important.
On the expertise aspect, long-term viability issues simply as a lot as short-term efficiency. Some instruments could also be closely marketed however face regulatory uncertainty or lack monetary stability. Taking the time to evaluate the platform’s maturity, funding sources, and compliance posture can assist keep away from surprises later. The objective isn’t simply to undertake AI—it’s to embrace it responsibly.
