What Happens When You Stop Building for Demos and Start Building for Real Work

Interview with Vitaliy Baklikov, CTO Skyward IT Solutions

Today we're joined by Vitaliy Baklikov, CTO at Skyward, a federal-first AI services and product company dedicated to building intelligent systems for the public good. From healthcare to compliance, Skyward empowers government agencies to adopt AI with confidence, transparency, and measurable impact.

Vitaliy is a results-driven technology leader with over 15 years of experience in enterprise systems architecture and large-scale data strategy. At Skyward, he heads dispersed engineering teams, focusing on secure, transparent, and reliable cloud-native AI solutions across Federal Agencies. His extensive expertise includes fintech, government, AWS, GCP, and Azure, and his work has received international recognition.

In this conversation, Vitaliy shares insights into building trust in public-sector AI, scaling intelligent agents within government infrastructure, and what it takes for engineers to navigate the unique challenges of deploying AI solutions in governmental contexts. \n \n What does a typical day look like for you as a CTO of a fast-growing company at the intersection of AI and federal modernization space?

My day typically revolves around ensuring my team is set up to succeed. I deliberately avoid micromanaging and instead of controlling my team focus on fostering an environment built on trust and independence. I start my day syncing with teams to discuss priorities, ongoing challenges, and strategies to deliver impactful AI solutions tailored for our government partners. My role involves strategic oversight. This means making sure we're aligned with our goals while navigating the complexities of integrating AI into government agencies that traditionally move slower than industries like fintech. Because of the nature of our clients, I spend significant time understanding their specific constraints and how we can innovate within those limitations. Also regular check-ins with my team, strategic planning sessions, and occasional client meetings define most of my day, along with dedicated periods of focused, uninterrupted work.

How do you build and manage a technical team capable of delivering mission-critical AI tools for government partners?

I have a simple but effective philosophy: "Hire for attitude, train for skill." By the time I interview candidates, their technical skills have usually been thoroughly vetted by my team. My focus is understanding if they have the right attitude and approach, mainly, are they independent thinkers? Will they accelerate our momentum, or slow us down? I invest heavily in building a culture of trust, giving my team the autonomy to execute and innovate without constant oversight. This has allowed us to consistently deliver mission-critical AI tools efficiently and effectively. I give my engineers the independence they need to own their work fully. It doesn’t mean they don’t make mistakes or I don’t make mistakes but when you hire for attitude, those mistakes make us better.

How do you ensure technical excellence without micromanaging your engineers?

Trust is at the core of my management style. I strongly believe in the capabilities of the people I hire. My approach is to clearly communicate expectations and give them the independence and resources they need to succeed. Of course, I step in to guide or assist when needed, but my role is primarily supportive. Ensuring technical excellence comes naturally when your team knows you trust their decisions and empower them to take ownership of their work.

How can young engineers develop the ability to earn trust in a team – even if they’re early in their careers?

It starts with attitude. Young engineers should focus on cultivating a proactive mindset, being open to learning, and demonstrating reliability. Trust builds from delivering consistently on promises, communicating transparently, and taking accountability for one's actions. Even early in their careers, those who are collaborative, approachable, and committed quickly stand out and become invaluable team members. At Skyward we have Sky Labs, where we hire junior engineers and help them come up to speed before they get to work on projects within Federal Agencies. Seeing them at work on internal projects really helps us build that trust.

From a CTO perspective, what challenges do you foresee in maintaining team innovation while dealing with strict governmental regulations and compliance requirements?

\The main challenge is balancing speed and innovation with the slow-moving nature of government compliance and legacy systems. Unlike fintech, government agencies often layer new technologies on outdated systems, creating a patchwork of complexities. And some days I wish we could just start from scratch. The key challenge is finding innovative ways to integrate AI while navigating regulatory frameworks, data security requirements, and compliance hurdles. Patience and strategic problem-solving are crucial, as innovation in this sector often involves incremental but impactful improvements rather than radical, overnight changes.

What’s your take on “AI for good” versus AI for enterprise? And where does government AI fit into that spectrum?

I see "AI for good" and enterprise AI not as opposites but as parts of a broader spectrum. Government AI occupies a unique place within this range. Ideally, it leverages enterprise-level innovation to deliver outcomes that positively impact citizens' lives. In my experience, especially reflecting on the efficiency I've seen in countries like Singapore, government AI has immense potential to transform societies for the better. At Skyward, our mission is to bridge the gap between advanced enterprise technology and meaningful public sector outcomes. For me, government AI represents an opportunity to apply cutting-edge tech in service of the public good.

:::info This story was published under HackerNoon’s Business Blogging Program.

:::

\