Jarvis Consulting Group launches Platform Engineering: a new capability dedicated to eliminating infrastructure chaos and embedding security, automation, and governance by design. 

Fragmented environments, manual deployments, and governance bolted on as an afterthought. These aren't edge cases; they're the reality for many organizations that rushed into the cloud and are now dealing with the operational consequences. 

At Jarvis Consulting Group, we are addressing this head-on with the launch of our new Platform Engineering practice, set under Technology Advisory Services. Leading the charge is Nikita Islamov, our Director of Data & Platform Engineering, a seasoned data and cloud engineer who has spent over a decade solving exactly these problems inside some of Canada's largest financial institutions. 

We sat down with Nik to understand what's broken, why it matters now, and what Jarvis is doing differently. 

1. What gap in the market or client need led Jarvis to launch this new practice? 

Honestly, this practice didn't come from a whiteboard exercise, it came from what we kept seeing on the ground with clients. What we recognized is that there's a real gap between organizations having cloud infrastructure and organizations operating it well. Jarvis is uniquely positioned to close that gap, not just by bringing in technical expertise, but by bringing a structured, opinionated approach to how infrastructure gets built and governed. That's what Platform Engineering is about. 

2. From your perspective, what has changed in the industry that makes this capability especially relevant today? 

A few things have converged at the same time. First, infrastructure as code has matured enormously. The tooling and practices are no longer experimental; they're standard capabilities. However, adoption hasn't kept pace with that maturity. Many organizations still treat infrastructure as code as a nice-to-have rather than the foundation for how they operate. 

Second, the cost pressure is real. Cloud bills ballooned during the adoption wave, and now leadership is asking hard questions about what they're actually getting. You can't answer those questions if your environments are inconsistent and your deployments are manual. 

And third, and this one is close to my heart, the security and governance expectations have fundamentally shifted. Regulators, auditors, and even customers expect that you know exactly who has access to what, and that your controls are embedded in the platform, not enforced through policy documents nobody reads. I spent years building data access control solutions: dynamic masking, fine-grained permissions, Unity Catalog governance. The organizations that got ahead of this weren't the ones with the most complex tooling; they were the ones that built security into the delivery pipeline from day one. 

3. What are the most common challenges you see organizations facing in this space today? 

When starting your cloud journey with platform engineering, you must define your scope first. Pick a few key features to focus on. This allows you to get them right and ensures a strong feedback loop. Once you have your base, you can expand into other features that address pressing business needs. Roles and responsibilities also need to be clearly defined; SRE, DevOps, and product teams all need to understand what they're accountable for. Finally, there should be clear definitions of your data governance policy based on your data security classifications, as product teams should not be left to interpret these policies differently. 

4. What misconceptions do leaders often have about this domain? 

The biggest misconception is that Platform Engineering is just "DevOps” with a fancier name. It's not. DevOps is a culture and practice around how software gets delivered. Platform Engineering is about building the internal product that makes that delivery possible: the paved roads, the golden paths, the self-service infrastructure that development teams can consume without needing to understand everything underneath it. 

Another misconception is that you need to boil the ocean before you see value. Leaders hear "standardize your entire infrastructure" and their eyes glaze over because they're picturing a two-year transformation program. The reality is that you can start with a single platform accelerator, such as a standardized landing zone, an automated pipeline template, or a governed data platform module, and begin generating value in weeks. You build momentum from there. 

Finally, there's a tendency to think of this as purely a cost-cutting exercise. It's not. Yes, you'll reduce waste and improve efficiency. But the bigger return is velocity. When your teams aren't fighting their own infrastructure, they build products. That's where the competitive advantage lives. 

5. How does this new practice fit into Jarvis' broader mission of Innovate. Empower. Impact.? 

It touches everything we stand for. 

Innovating: we're bringing modern, opinionated approaches to infrastructure delivery that most organizations haven't encountered in a consulting context. We're not just recommending tools; we're bringing accelerators, reference architectures, and proven patterns that compress time-to-value. 

Empowering: this is the pillar that resonates most with me personally. When you build a well-designed internal platform, you're not creating dependency on a consulting team. You're giving the client's own engineers the tools and structure to move faster, with the confidence that comes from working within a well-governed platform. That's empowerment in the truest sense. My goal is always to leave teams in a better position than we found them. 

Making an impact: the outcomes are concrete. Faster deployments, fewer incidents, cleaner audit trails, better security posture. These aren't soft benefits; they're things that show up on scorecards and in board conversations. 

6. What makes Jarvis' approach in this area different from traditional consulting models? 

Traditional consulting in this space tends to be either highly prescriptive, as in "here's the framework, go implement it," or it's staff augmentation dressed up as consulting. Neither of these solve the problem. 

What we're building is different because it's grounded in real delivery. I've built many of these systems before, having managed Hadoop clusters at enterprise scale, built access control solutions from scratch, and led Azure Purview adoption across a major bank. When I walk into a client conversation, I'm not working from a slide deck; I'm drawing on problems I've previously solved. That shapes how we scope engagements, how we build our accelerators, and how we measure success. 

We're also staying closely connected to the broader Jarvis ecosystem, including the Data practice and the AI work that Holly Heglin and her team are driving. Platform Engineering doesn't exist in isolation. A well-governed, well-engineered platform is the foundation that makes AI initiatives possible. That integration is a real differentiator. 

7. What types of projects or initiatives will this practice focus on? 

The scope of this practice is still taking shape. There is a lot of interest out there, and we're hearing about a wide range of potential use cases — from architecture reviews and standing up initial landing zones, to overhauling governance solutions and executing application and data migrations. We're still finding our identity as a practice, and we're deliberately taking the time to explore the landscape before locking in our focus areas. 

8. How do you see this practice evolving as organizations continue to adopt new technologies? 

Things may get harder before they get easier. With AI emerging across every industry, more companies are trying to leverage the capability without fully appreciating that it's still maturing. While AI can certainly supplement elements of the work, the finer decisions should still be made by qualified people who understand the requirements and their implications. We will need domain experts who can assess the impact of AI on automation, especially as infrastructure as code becomes the gold standard. 

9. What drew you personally to this field, and what keeps you excited about working in it today? 

My love for creating/building things was sparked at an early age by LEGOs. I used to spend hours constructing anything my mind could come up with, first following the instructions, then tearing it all down, mixing everything together, and creating something entirely new. When I got into computer science, that same instinct fused with a fascination for automation. When I finally reached the real world and got some experience under my belt, I found I could apply that same creative drive to real world problems. When I got to design my first framework, I knew this was something I wanted to continue to do!