Principal Cloud Support Engineer

Wasabi establishes AI business in Silicon Valley, taps Pinaki Mukherjee to lead as senior vice president & general manager. Semiconductor and storage veteran to lead dedicated AI business to accelerate the independent storage foundation for AI labs, startups, and neocloud push as data demand grows to unprecedented scale. Sep 10, 2026 Prev Next 1 of 43,611 Wasabi Technologies, the hot cloud storage company, announced the formation of a dedicated AI business, and the appointment of semiconductor and storage veteran Pinaki Mukherjee as senior vice president and general manager to lead it. Wasabi stores hundreds of petabytes of AI data for frontier model labs, generative AI startups, and neocloud compute providers worldwide. This new AI business brings dedicated strategy, partnerships and go-to-market focus for this demand as AI infrastructure matures. "Mukherjee has a track record of driving the kind of high-value partnerships that move markets, and that's exactly what this moment requires," said Marty Falaro, president and COO of Wasabi. "AI workloads are pushing storage demand to a scale we've never seen, and Mukherjee is the right person to build the partnerships that extend Wasabi's position as the industry's choice for cloud storage, at the exact moment inference is reshaping what that storage needs to do." Proven leadership in the heart of Silicon Valley Mukherjee brings more than 20 years of experience building technology ecosystems across semiconductors, storage, and AI infrastructure. He will lead Wasabi's AI strategy, partnerships, and go-to-market efforts from Silicon Valley. His track record includes: * Over $2 billion in partnership-driven revenue and more than $10 billion in strategic M&A and investment outcomes * Senior business strategy and corporate development roles at Fungible, Druva, and Western Digital * Leading semiconductor strategy and AI infrastructure engagements at Alvarez & Marsal, a global consulting firm Why AI demand is remaking the storage market Storage has become one of the most strategic line items in AI infrastructure budgets. AI training reads the same datasets tens or hundreds of times over, and inference pipelines move data continuously between storage and GPU compute. Hyperscaler cloud pricing models haven't kept pace with how AI actually operates: data that needs to move freely, repeatedly, and unpredictably across environments. Avoiding vendor lock-in has become a deliberate strategy in its own right as companies want the freedom to adopt new infrastructure as the market shifts, without their own data becoming the obstacle. Wasabi's framework optimizes storage across the entire AI lifecycle, so data moves freely to wherever compute lives, at a flat, predictable cost with no egress or API fees, and no vendor lock-in. Under Mukherjee's leadership, Wasabi will bring this framework to the AI industry at scale. "AI customers don't need another hyperscaler, they need the freedom to move their data wherever their workloads take them, without egress fees, API fees, or lock-in dictating their architecture," said Mukherjee. "Wasabi is already the independent choice that innovative enterprises, neoclouds, and data platforms turn to as they scale beyond what any single hyperscaler ecosystem can offer. I'm looking forward to building the ecosystem that scales that freedom across the AI ecosystem." Built over a decade, delivering ROI at petabyte scale Wasabi has spent a decade building the infrastructure that now stores petabytes of AI data for customers globally, supported by 16 storage regions worldwide, 18,000 channel partners, and over $700 million in funding to date. Together with its Megaport partnership and growing portfolio of developer and agentic AI capabilities, including Wasabi MCP, Wasabi continues to expand its role in AI infrastructure. As autonomous AI agents take on more of the data lifecycle, including retrieving training sets, checkpointing intermediate results, and moving data between compute environments without human intervention, having a predictable cost structure is even more critical. Storing AI data with Wasabi ensures agents can read, write, and move data as often as a task requires without every API call becoming a hidden cost. Recent deployments show the ROI: * An image- and video-generation lab migrated 175 petabytes off a hyperscaler within months * A robotics data consortium has stored multiple petabytes while projecting annual savings of over JPY 100 million.

Wasabi Technologies has launched a dedicated AI business unit and appointed Pinaki Mukherjee as senior vice president and general manager to lead it from Silicon Valley. The Boston-based cloud storage company stores hundreds of petabytes of AI data for frontier model labs, generative AI startups, and neocloud compute providers globally. Mukherjee brings over 20 years of experience in semiconductors, storage, and AI infrastructure. His track record includes driving over $2 billion in partnership revenue and more than $10 billion in strategic M&A and investment outcomes. He previously held senior roles at Fungible, Druva, and Western Digital. Wasabi has raised over $700 million in funding to date and operates 16 storage regions worldwide. Recent deployments include an image-generation lab migrating 175 petabytes and a robotics data consortium projecting annual savings exceeding JPY 100 million.

How healthcare keeps control in hybrid cloud video. For hospitals and health systems, the real privacy question isn't where video lives. It's who controls it. For a hospital evaluating hybrid or cloud video, the concern is rarely about the technology itself. It's about losing the ability to say who accessed the video, and when. The assumption is direct: move to the cloud, and control shifts to someone else's servers, somewhere the organization can no longer reach. That assumption is common in regulated environments, and it's usually enough to stall a conversation before it gets to the details that actually matter. It's also the wrong place to start. The real question isn't where the video lives. It's who controls it: who owns it, who can access it, how that access is authenticated, how the data is protected at rest and in transit, and who ultimately decides where it's stored. For a healthcare organization weighing HIPAA obligations against the appeal of cloud-based management, that reframe changes the entire conversation. Why compliance and IT need a seat at the table before the VMS is selected. The biggest mistake is treating video surveillance as a siloed security purchase, a framing that's becoming less accurate every year. Today's VMS touches the network, identity management, cloud infrastructure, cybersecurity policies, storage, and potentially regulatory requirements. When IT or legal gets involved only after the system has already been selected, the result is retrofitting answers around data residency, retention, authentication, and remote connectivity. Getting stakeholders to the table early creates more questions at the front end, but it prevents much bigger problems downstream. An architecture built to keep video under the organization's control. Once those stakeholders are in the room and the location assumption gets corrected, the conversation tends to open up. With CompleteView, video can stay on the hospital's own recording infrastructure while Salient Cloud Services adds secure remote access, health monitoring, and management, without requiring that video ever leave the premises. If cloud storage makes sense for disaster recovery or longer retention down the road, that's handled separately through Salient's partnership with Wasabi, as an optional service rather than a default. What resolves the concern isn't a case for cloud being safe. It's showing hospitals they have choices. That choice, not a forced switch to one model or the other, is the deciding factor in healthcare deployments. Most customers aren't resistant to cloud technology; they're resistant to being told it's all-or-nothing. Being able to tell a hospital it can keep its on-premises recording environment while still gaining secure cloud-based remote access, management, and monitoring has settled more than one stalled deal. HIPAA doesn't come from the architecture. It comes from what the organization can prove. Healthcare organizations are working within HIPAA, and no deployment model makes an organization compliant by default. That holds whether the framework in question is HIPAA, CJIS, or a state privacy law. What matters is whether the organization can demonstrate the appropriate controls around access, encryption, retention, auditing, and evidence handling. CompleteView supports that demonstration through capabilities like centralized user management, Active Directory integration, per-camera retention policies, and optional storage encryption, but the hospital is still required to operate those controls responsibly. The platform can support a compliance strategy; it can't substitute for one. That responsibility extends to the basics that are too easy to overlook: who gets access, what permissions they're granted, and what happens to that access the day someone leaves the organization. A cloud provider secures its infrastructure; it doesn't manage a hospital's user accounts. What video access control needs to look like under HIPAA. As healthcare organizations get more sophisticated about privacy, the question they ask tends to shift. It stops being "who can access my video?" and starts being "can I tell who accessed my video?" That distinction matters under HIPAA's audit-control expectations specifically. It's about being able to prove, after the fact, exactly who was in the system and what they did. In practice, that means granular permission management, Active Directory integration, secure remote access, and accountability for how the system gets used, including protection for recorded and exported evidence throughout its lifecycle, not just while it sits in primary storage. The goal is to ensure that only authorized users have the access they actually need, and maintaining control of sensitive video throughout its lifecycle, not just keeping unauthorized people out. Three questions healthcare buyers should add to every VMS RFP. Three questions should be standard in a healthcare VMS RFP, but usually aren't: * Where can my video be stored, and how much control do I have over that decision? * How does the platform protect identity, access, encryption, retention, and exported evidence? * If my requirements change in three to five years (new regulatory guidance, a new retention policy, a new EHR integration), can the architecture change with me, without forcing me to replace everything I've already invested in? The last question gets overlooked most often. Regulatory guidance, retention requirements, and the technology itself will continue to evolve. A healthcare organization should select an architecture that gives it room to adapt, not one that locks it into today's requirements. What holds up under scrutiny. Physical security is increasingly part of the broader cybersecurity and privacy conversation healthcare IT teams are having. Expect more scrutiny over who has access to surveillance video, where copies of it exist, how long it's retained, how it's protected, and how the organization responds when a vulnerability is identified. The organizations that hold up under scrutiny won't be the ones that picked the safest-sounding deployment model. They'll be the ones that can answer a simple question with confidence: not where is its video, but who controls it, and can Salient Systems Corporation prove it. That's the standard a hybrid architecture, built around choice rather than a forced trade-off, is designed to meet.