V2 AI hires ex-HashiCorp director Arseny Chernov to lead Singapore push

V2 AI has appointed Arseny Chernov as Director, Forward Deployed Engineering – Applied AI, a hire that anchors the consultancy's regional hub in Singapore as it expands across Asia-Pacific. The announcement, dated 12 November 2026, signals where the firm thinks the next phase of enterprise AI work will happen: not in labs or hackathons, but in the unglamorous engineering that turns a working prototype into a system a bank or telco can actually run.

Chernov's remit covers Singapore and South-East Asia. He will work directly with customers and with V2 AI's internal technical teams on three things the company names explicitly: AI architecture, forward deployed engineering, and secure multi-agent workflows. That last item is worth pausing on. Multi-agent systems — where several AI components hand work to one another — are fast becoming the default shape of enterprise AI deployments, and securing them is an unsolved problem for most buyers. V2 AI is effectively hiring for the gap between what AI vendors demo and what regulated businesses will sign off on.

Why does this hire matter now?

The timing tracks a shift the whole industry is working through. Companies across the region are trying to move AI projects out of pilot stages and into live business use, and many are hitting the same wall: practical problems around data, governance, and infrastructure that only appear once a system has to scale across a larger operation. A pilot can run on a clean dataset and a tolerant stakeholder. Production cannot.

That's the market V2 AI is positioning itself in. Founded in 2023, the firm operates across Sydney, Melbourne, Brisbane, Perth, Singapore, and Kuala Lumpur — an Australian base with a deliberate South-East Asian extension. The company calls its Singapore expansion a key part of its regional growth strategy, tied to rising demand for applied AI work in South-East Asia.

Chernov's own framing, in a statement released with the appointment, puts the challenge plainly:

"Organisations are moving beyond AI experimentation, but getting from a promising prototype to a reliable enterprise solution requires strong data foundations, robust architecture, co-design with security and governance, alongside with uncompromising focus on measurable business outcomes," Chernov said.

Every clause there names a real failure mode. Weak data foundations sink models in production. Architecture that wasn't designed for governance gets rebuilt later at higher cost. And AI projects without measurable business outcomes are the ones that quietly get shelved after the pilot review. His point is that these constraints have to be co-designed in from the start, not bolted on.

Who is Arseny Chernov?

His career reads like a preparation course for exactly this job. Most recently, Chernov was Regional Director for ASEAN, Korea, and Greater China at HashiCorp, the infrastructure software company. There he led regional technical teams and worked with organisations on AI-native security, governance, and regulatory practices — the same bundle of concerns he'll now handle for V2 AI's customers, since enterprises adopting AI face security and compliance questions that look a lot like the ones infrastructure buyers faced a few years ago.

Before HashiCorp, he spent more than five years at Google in senior technical and engineering roles across Asia-Pacific and the US. Two parts of that stint stand out. He worked on software releases and programmes linked to Google Payments — payment systems being among the most tightly regulated, reliability-obsessed software environments that exist. And he supported enterprise customers and strategic partners on cloud transformation projects, including early generative AI work. That means he was in the room for the first wave of enterprise generative AI, before most organisations had a strategy for it.

In between Google and HashiCorp, Chernov led Partner Solutions Architecture for Asia-Pacific and Japan at Databricks, the data and analytics platform. He joined as the company's first hire in Singapore — a detail that matters here. He has already done, at Databricks, precisely what V2 AI is asking him to help do now: establish a technical presence in Singapore from essentially nothing, building a regional network of more than 50 strategic technology partners while working on data and machine learning pipelines for regulated businesses.

That resume — Google, Databricks, HashiCorp — covers the full stack of what enterprise AI deployment requires: cloud infrastructure, data platforms, and security governance. Takeaway: V2 AI didn't hire a generalist executive; it hired someone who has built each layer of the stack it sells.

What will he actually do?

The role focuses on helping enterprise customers turn new AI tools into production systems. In practice, that means addressing the security, governance, and operational constraints that emerge when organisations move beyond experimentation — the point where enthusiasm meets audit requirements, data-residency rules, and uptime expectations.

Forward deployed engineering, the discipline named in his title, is a model popularised by AI companies that embed engineers directly with customers rather than shipping a product and hoping it fits. The approach makes sense for AI in particular, because every enterprise's data, legacy systems, and risk appetite are different enough that off-the-shelf deployments routinely fail. Chernov will sit at that boundary between V2 AI's internal technical teams and its customers' realities.

His second statement on the appointment points at how V2 AI intends to compete:

"V2 AI has the technical depth and proven enterprise deployments experience to help organisations navigate such journeys. I'm excited to work alongside the team and our customers to build AI solutions that are practical, secure and capable of delivering lasting value."

The claim to rest on is proven deployments — in a market saturated with AI consultancies making similar promises, track record is the differentiator buyers can actually verify.

What does the leadership say?

Williams — quoted in the company's statement on the appointment — framed the hire as a response to what the regional AI market now demands:

"Successfully deploying AI at enterprise scale requires a combination of deep technical expertise, an understanding of complex operating environments and the ability to turn emerging capabilities into practical business outcomes."

Williams went on to argue that Chernov is unusually well matched to those demands:

"Arseny brings an exceptional combination of experience across some of the world's leading technology companies, along with a strong track record in enterprise architecture, forward deployed engineering and strategic partnerships. His appointment strengthens our Singapore team and our ability to help organisations move from AI ambition to real-world implementation."

The phrase "from AI ambition to real-world implementation" is effectively the company's thesis in six words. V2 AI is betting that the bottleneck in Asia-Pacific AI adoption is no longer interest or budget — it's execution capacity, and firms that can supply it will grow with the market.

Is Singapore the right battleground?

The geography of the hire tells its own story. V2 AI already spans six cities, but it's choosing Singapore as the hub for South-East Asia, and Singapore is where multinational vendors typically anchor regional technical operations — talent density, favourable regulation, and proximity to customers in Indonesia, Thailand, Vietnam, Malaysia, and the Philippines. Chernov's patch at HashiCorp covered ASEAN, Korea, and Greater China; his network across those markets comes with him.

For V2 AI, the calculation is straightforward. South-East Asian enterprises are past the experimentation phase and are now budgeting for deployment — the stage where consultancy revenue is largest and stickiest, because production systems need continuous engineering rather than one-off advisory work. A hire who has opened a Singapore office before, built a 50-partner network, and worked with regulated businesses on AI governance addresses the exact risk profile of that bet.

The open question is competition. Every major consultancy and every hyperscaler's professional services arm wants the same enterprise AI deployment work in the same region. V2 AI's counter, per its own statements, is technical depth and a forward-deployed model that puts engineers inside customer operations. Whether that beats incumbents' scale will play out over the next year — but with Chernov in place, the firm now has a deployment veteran running its most important growth market.