Full-Time
Cost-efficient Kafka-compatible streaming platform
$194.4k - $228.8k/yr
Remote in USA + 1 more
More locations: Remote in Canada
Remote
Remote within the United States or Canada, with 30–50% travel during active engagements and on-site customer work.
See people who can refer or advise you
Redpanda provides a streaming data platform compatible with Kafka APIs, offered as a fully managed cloud service or a self-hosted deployment. It ingests, stores, and serves real-time data—events, logs, and messages—so applications can react quickly. It differentiates itself by reducing infrastructure costs and resource use, offering both cloud and on-prem options, and is Jepsen-verified for safety. Its goal is to deliver practical, cost-efficient, easy-to-deploy streaming with low latency and high throughput while integrating with existing tools.
Company Size
201-500
Company Stage
Series D
Total Funding
$265.5M
Headquarters
San Francisco, California
Founded
2019
See people who can refer or advise you
Help us improve and share your feedback! Did you find this helpful?
Remote Work Options
Flexible Work Hours
HPE launches Vera CPU server for agentic AI. At COMPUTEX 2026, Hewlett Packard Enterprise (HPE) (NYSE: HPE) announced the expansion of its server portfolio with the launch of the HPE ProLiant Compute DL394 Gen12, a new CPU server powered by NVIDIA's Vera CPU architecture. The company said the platform has been purpose-built to address the growing computational demands of agentic AI, high-performance data processing, and latency-sensitive enterprise workloads. The new server was introduced as part of a collaboration involving HPE, NVIDIA, and Redpanda, with the technology also being explored by the New York Stock Exchange (NYSE) to support large-scale market infrastructure operations. According to HPE, the HPE ProLiant Compute DL394 Gen12 has been engineered specifically for emerging agentic AI applications, which require real-time reasoning, rapid data processing, and highly responsive infrastructure. The company said the platform combines high CPU performance, increased memory bandwidth, low latency, and enterprise-grade security to support next-generation AI deployments. "The shift from generative models to agentic systems is redefining the role of compute across the enterprise," said Antonio Neri, president and CEO of HPE. He noted that organizations increasingly require infrastructure capable of handling real-time decision-making and reasoning workloads across AI and financial services applications. The server is based on NVIDIA Vera CPUs and adopts a monolithic processor design rather than conventional high-core-count chiplet architectures. HPE stated that this approach helps avoid non-uniform memory access (NUMA) challenges commonly associated with multi-processor environments, where latency variations can impact performance consistency. A key feature of the platform is its use of LPDDR5X memory technology, a low-power form of dynamic random-access memory (DRAM). According to HPE, the server delivers an aggregate memory bandwidth of 1.2 terabytes per second, equivalent to up to 14 gigabytes per second per core. This architecture is intended to enable faster ingestion and processing of large datasets while improving resource utilization for AI workloads. NVIDIA positioned Vera as a CPU architecture developed specifically to support AI-centric computing environments. "Agentic AI has arrived, and it needs a new CPU," said Jensen Huang, founder and CEO of NVIDIA. He stated that Vera was designed to orchestrate AI factories and deliver improved efficiency and faster task completion compared with traditional x86-based systems. The technology is also being evaluated within financial market infrastructure. Lynn Martin, President of NYSE Group, said the exchange processes more than 1.1 trillion messages each day and is exploring the use of NVIDIA Vera CPUs, in collaboration with Redpanda and HPE, to further optimize latency, throughput, and system reliability. Beyond performance enhancements, HPE emphasized the server's security architecture. The HPE ProLiant Compute DL394 Gen12 incorporates the company's Silicon Root of Trust technology and integrates HPE Integrated Lights-Out (iLO) 7 management capabilities. The platform also includes a secure enclave architecture designed to protect systems throughout their operational lifecycle. According to HPE, the new generation of ProLiant servers is the first to meet the National Institute of Standards and Technology's quantum-resistant security requirements, a development aimed at helping organizations prepare for future cybersecurity challenges and safeguard sensitive workloads in regulated industries. The server also integrates HPE Compute Ops Management, a cloud-based management platform that provides centralized visibility and automation across distributed server environments. HPE said the solution leverages AI-driven operational insights to simplify infrastructure management, reduce administrative effort, and help minimize downtime-related business disruptions.
Redpanda, a provider of data and agent governance infrastructure, has reported 70% year-over-year ARR growth in its first quarter of fiscal 2027. The company closed its highest number of seven-figure deals in a single quarter and appointed three senior executives: Kyle Corcoran as CFO, Melissa Czapiga as CMO, and Raghu Nandan as VP of Product. The company has expanded its Agentic Data Plane with centralised AI gateway capabilities, observability and unified authentication. Redpanda delivered what it calls the industry's first adaptable streaming engine, allowing dynamic optimisation between ultra-low latency and high-throughput at topic level. The company has opened new offices in San Francisco and Austin, partnered with NVIDIA on agentic AI infrastructure, and joined Akamai's Qualified Compute Partner Programme.
Redpanda has launched Salesforce connectors enabling real-time, bidirectional data integration between Salesforce and enterprise data systems. The native processors bypass traditional middleware and support continuous data streaming into and out of Salesforce. The connectors aim to close the gap between CRM data and operational systems, potentially positioning Salesforce as a central data hub for enterprises. As companies increasingly focus on real-time decision-making across sales and operations, demand for tighter data streaming could influence how the platform fits within technology stacks. Salesforce shares currently trade at $170.85, approximately 38% below the average analyst target of $273.85. The key risk is that customers may continue using existing middleware or rival platforms for data streaming, potentially limiting adoption of the new integration.
Redpanda has launched four new enterprise connectors for Redpanda Connect: Amazon DynamoDB change data capture input, Oracle CDC input, and Salesforce processor and output components. The connectors enable real-time data streaming from critical enterprise systems without traditional middleware infrastructure. The new components address integration challenges in key enterprise systems. The DynamoDB CDC connector automates shard management for e-commerce and gaming platforms, whilst the Oracle CDC connector eliminates the need for dedicated Kafka Connect clusters. The Salesforce connectors enable bidirectional data flow between CRM and data ecosystems. Redpanda Connect is designed to run in Kubernetes environments and uses declarative YAML configuration. The platform has added over 40 connectors in the past year, enabling faster deployment of streaming pipelines for AI and event-driven applications.
Redpanda brings identity, policy control, and data governance to AI agents. Redpanda announced the availability of new core capabilities in the Redpanda Agentic Data Plane (ADP), including a centralized AI gateway, AI observability and evaluation via OpenTelemetry, AI agents, and unified authentication and authorization. Together, these features form a unified governance layer that allows enterprises to securely connect AI agents and Model Context Protocol (MCP) servers to live enterprise data with visibility and control. As organizations move from AI experimentation to production, the challenge has shifted from building agents to governing them. "This is why the enterprise agentic AI market is struggling while consumer AI flourishes," said Tyler Akidau, CTO of Redpanda. "Building an agent is remarkably easy. Running one safely in a company, with access to sensitive systems and data, remains genuinely hard. Redpanda is focused on bringing control to the connectivity layer - rather than configuring access policies individually at each data source, enterprises need a central point through which all agent interactions flow: an agentic data plane." "AI agents don't fail because models are bad; they fail because systems lack control," said Alex Gallego, founder and CEO of Redpanda. "With Redpanda Agentic Data Plane, we're giving enterprises a practical way to operate agentic systems safely, with identity, policy enforcement, and observability built in from day one." Available Redpanda ADP capabilities. First introduced in October, Redpanda's ADP exists to make AI agents trustworthy at scale. Acting as both a governance layer and a control plane, it governs how agents authenticate, access data, and take action while recording intent, inputs, and outputs for complete auditability. With AI Gateway, open agent interoperability, unified identity, and full observability, enterprises gain the controls needed to safely run agents on live data without sacrificing speed or visibility. "Redpanda addresses the right requirements with this release, as our research shows a strong need for both strong AI governance and real-time data inputs," says Kevin Petrie, VP Research and Head of Data Management Practice of BARC. "AI adopters feel overwhelmed with the complex task of meeting these requirements while safely integrating powerful GenAI models into their business processes. Redpanda's approach will help make data and AI leaders' lives easier." AI Gateway. Redpanda AI Gateway provides a unified access layer between applications, AI models, and MCP services. It centralizes routing, policy enforcement, cost controls, and observability across all AI traffic. Enterprises can define token budgets, set spending limits, and optimize usage through deferred tool loading, bringing operational discipline to complex agent workflows. The AI Gateway also serves as a central point to aggregate and govern MCP servers, with an admin-controlled registry of approved servers and YAML-based configuration for rapid deployment. AI agents. Redpanda ADP is designed to work with any AI agent framework. Enterprises can run and govern agents built on their existing frameworks, as well as use Redpanda's built-in AI agents when they want a fully-managed option. All agents, whether hosted by Redpanda or external, interact with data and tools through open standards like the A2A protocol, and integrate with ADP's unified authentication, authorization, and observability services. Agents can also be triggered through Redpanda Connect pipelines, enabling real-time, event-driven and human-in-the-loop workflows. Unified authentication and authorization. All components of the Redpanda Agentic Data Plane are secured through OIDC-based identity and fine-grained authorization policies. Every request, whether from a user, service account, or agent, is authenticated and governed, eliminating long-lived credentials and reducing the risk of uncontrolled agent access. End-to-end observability and evaluation. Redpanda ADP emits full-fidelity metrics, traces, logs, and transcripts using the OpenTelemetry Protocol (OTLP). Enterprises can inspect agent behavior directly in the Redpanda console or export traces to external observability platforms, enabling debugging, compliance, and post-incident analysis. The Redpanda Agentic Data Plane is built on a low-latency streaming foundation, enabling real-time data access, continuous context updates, and event-driven agent execution. With more than 300 connectors available through Redpanda Connect, enterprises can expose data from databases, SaaS platforms, data streams, and data lakes without moving data or breaking existing architectures. More about