Skip to main content

SignalFx Opens Research and Development and Support Office in Poland

SignalFx announced the opening of a new Research, Development and Support Office in Krakow, Poland and the addition of Martin Burlinski, Head of Engineering, EMEA.

The new Krakow facility will enable SignalFx to accelerate product development and provide broader global support for its customers.

“We were naturally attracted to Krakow not only because of its strong existing talent pool of world-class engineers but also its proximity to recent graduates from the city’s many universities,” said Leonid Igolnik, EVP Engineering for SignalFx. “We have an immediate need for engineers to become a core part of our company working side-by-side with our Silicon Valley and Research Triangle Park teams. With a global client base and the industry’s only streaming analytics, NoSample™ architecture we need to continually push the boundaries of what’s technically possible to operate in a real-time world.”

SignalFx offers a highly differentiated and technically advanced monitoring platform optimized for today’s increasingly complex cloud-native environments. It incorporates innovations like end-to-end streaming analytics that finds problems in real time, and a NoSample™ architecture based distributed tracing solution that observes every single transaction and isolates all outliers instead of just a small subset. Innovations such as these help developers rapidly spot issues and initiate fixes before they impact customers.

“It’s critical that our customer service meets the real-time demands businesses face,” said Matt Stone, Director Global Technical Support, SignalFx. “Our new Krakow facility dramatically expands our time zone coverage, supporting our rapidly growing EMEA and APAC markets, and takes us toward a 24/7 model.”

SignalFx has immediate openings in Krakow for the following positions:

Software Engineering
System Testing
Production Engineering
Customer Success Engineering
Technical Support
Cloud Security

“We are opening an office in Krakow that will not only do cutting-edge work but also will evoke the cool look and feel of what you might find in California,” said Burlinski. “Our engineers will feel immersed both in the work and culture of Silicon Valley.”

Burlinski brings experience from building some of the largest business-to-business software-as-a-service products in the world with companies like Taleo and Oracle and has extensive product development experience in Canada, Silicon Valley and Poland. Most recently at Oracle, Mr. Burlinski grew the Krakow office from a small team to a sizable multi-disciplinary organization.

The Latest

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

SignalFx Opens Research and Development and Support Office in Poland

SignalFx announced the opening of a new Research, Development and Support Office in Krakow, Poland and the addition of Martin Burlinski, Head of Engineering, EMEA.

The new Krakow facility will enable SignalFx to accelerate product development and provide broader global support for its customers.

“We were naturally attracted to Krakow not only because of its strong existing talent pool of world-class engineers but also its proximity to recent graduates from the city’s many universities,” said Leonid Igolnik, EVP Engineering for SignalFx. “We have an immediate need for engineers to become a core part of our company working side-by-side with our Silicon Valley and Research Triangle Park teams. With a global client base and the industry’s only streaming analytics, NoSample™ architecture we need to continually push the boundaries of what’s technically possible to operate in a real-time world.”

SignalFx offers a highly differentiated and technically advanced monitoring platform optimized for today’s increasingly complex cloud-native environments. It incorporates innovations like end-to-end streaming analytics that finds problems in real time, and a NoSample™ architecture based distributed tracing solution that observes every single transaction and isolates all outliers instead of just a small subset. Innovations such as these help developers rapidly spot issues and initiate fixes before they impact customers.

“It’s critical that our customer service meets the real-time demands businesses face,” said Matt Stone, Director Global Technical Support, SignalFx. “Our new Krakow facility dramatically expands our time zone coverage, supporting our rapidly growing EMEA and APAC markets, and takes us toward a 24/7 model.”

SignalFx has immediate openings in Krakow for the following positions:

Software Engineering
System Testing
Production Engineering
Customer Success Engineering
Technical Support
Cloud Security

“We are opening an office in Krakow that will not only do cutting-edge work but also will evoke the cool look and feel of what you might find in California,” said Burlinski. “Our engineers will feel immersed both in the work and culture of Silicon Valley.”

Burlinski brings experience from building some of the largest business-to-business software-as-a-service products in the world with companies like Taleo and Oracle and has extensive product development experience in Canada, Silicon Valley and Poland. Most recently at Oracle, Mr. Burlinski grew the Krakow office from a small team to a sizable multi-disciplinary organization.

The Latest

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...