Bedrock Data

Frictionless Data Security for the GenAI Era

As organizations rapidly adopt Generative AI, the volume of data being ingested, processed, and generated is exploding. With this proliferation comes an unprecedented challenge: how to secure sensitive data across fragmented clouds, SaaS applications, and AI systems without slowing down innovation. Bedrock Data, formerly known as Bedrock Security, was incubated with Greylock to solve exactly this problem. By introducing the industry's first Metadata Lake, Bedrock Data provides a living, continuous map of an organization's data—detailing what it is, where it resides, who is accessing it, and its sensitivity level—without ever requiring the data itself to be moved.

For enterprise customers, this means transitioning from legacy, disruptive Data Loss Prevention (DLP) tools to a modern, autonomous architecture. Instead of relying on manual classification, security teams can leverage Bedrock's AI-native platform to make data protection continuous and invisible. Backed by a $25 million Series A round led by Greylock, and founded by veterans from Sumo Logic, Rubrik, and Cohesity, Bedrock Data is positioned to redefine Data Security Posture Management (DSPM) for Fortune 1000 organizations and beyond.

The stakes for data security have never been higher. As artificial intelligence models require massive datasets for training and inference, the attack surface for potential data breaches expands exponentially. Traditional security perimeters are no longer sufficient when data is constantly flowing between on-premises databases, multi-cloud environments, and third-party AI vendors. Bedrock Data's innovative approach addresses this reality by decoupling data visibility from data movement. By analyzing metadata rather than the underlying data payloads, the platform ensures that organizations can maintain strict governance and compliance without introducing latency or violating privacy regulations.

Furthermore, the shift towards AI-driven business processes necessitates a security posture that is as dynamic as the technologies it protects. Bedrock Data's platform continuously monitors data access patterns, identifying anomalies and potential threats in real-time. This proactive approach empowers security teams to mitigate risks before they escalate into full-blown incidents. The company's vision extends beyond simple data discovery; it encompasses a holistic understanding of data lineage, usage, and risk, providing security leaders with the actionable intelligence they need to make informed decisions in an increasingly complex threat landscape.

A Culture of Autonomous Innovation

At Bedrock Data, the engineering and operational culture revolves around removing friction. The team believes that data is the lifeblood of modern organizational growth, and that security measures should integrate seamlessly with business operations rather than acting as roadblocks. This philosophy translates into a culture of autonomous innovation, where engineers and product builders are encouraged to design systems that work intelligently in the background.

Because the company is tackling complex challenges in AI risk governance and entitlement chain analysis, there is a strong emphasis on deep technical fluency and cross-functional collaboration. Employees are expected to thrive in a high-growth, startup environment where they actively participate in discovering new solutions for a disruptive category. The environment is fast-paced, collaborative, and driven by a shared mission to shape the future of enterprise data security.

Innovation at Bedrock Data is not just a buzzword; it is a core operational principle. The engineering team operates with a high degree of autonomy, empowered to explore novel approaches to metadata analysis and machine learning. This requires a unique blend of creativity and analytical rigor, as engineers must balance the need for rapid experimentation with the uncompromising reliability required of enterprise security products. The culture encourages intellectual curiosity and continuous learning, recognizing that the threat landscape is constantly evolving and that yesterday's solutions may not be sufficient for tomorrow's challenges.

Collaboration is also deeply ingrained in the company's DNA. Building a platform that spans cloud infrastructure, data engineering, and cybersecurity requires seamless communication across diverse technical disciplines. Engineers work closely with product managers, security researchers, and go-to-market teams to ensure that the platform not only meets technical requirements but also addresses the real-world pain points of CISOs and security practitioners. This cross-functional alignment fosters a shared sense of ownership and accountability, driving the entire organization towards a common goal of redefining data security for the AI era.

What You'll Actually Do

Working at Bedrock Data means being at the forefront of the GenAI and cloud security intersection. The roles are dynamic and require a mix of strategic thinking and hands-on execution.

For Engineers, you will be building and scaling the core Metadata Lake architecture. Whether you are a backend engineer optimizing data ingestion pipelines or a full-stack engineer developing intuitive interfaces for CISOs, your work will directly impact how enterprises visualize and protect their data. You will tackle complex problems related to data classification, AI governance, and cloud infrastructure integration. The technical challenges are immense, requiring expertise in distributed systems, high-performance computing, and advanced data processing techniques. You will be tasked with designing architectures capable of handling petabytes of metadata in real-time, ensuring that the platform remains highly available, scalable, and resilient under extreme loads.

Beyond the core infrastructure, engineers are also involved in developing the machine learning models that power Bedrock Data's autonomous classification and threat detection capabilities. This involves working with massive datasets to train and refine algorithms, ensuring that they can accurately identify sensitive information and anomalous behavior across diverse enterprise environments. The work requires a deep understanding of both cybersecurity principles and data science methodologies, bridging the gap between theoretical research and practical application.

For Go-To-Market & Sales professionals, such as Enterprise Account Executives or Sales Engineers, your focus will be on market expansion and evangelism. You will engage with CISOs, Chief Data Officers, and VPs of Engineering at Fortune 1000 companies, helping them understand the shift from traditional security postures to Bedrock's data-centric approach. You will manage complex sales cycles and build strategic partnerships within the cloud ecosystem (e.g., AWS, Snowflake). This role requires not only exceptional sales acumen but also a deep technical understanding of enterprise architecture and security compliance frameworks. You will serve as a trusted advisor to senior executives, guiding them through the complexities of securing data in the age of generative AI.

For Product & Marketing teams, you will align the product roadmap with the needs of large enterprise accounts, translating complex technical capabilities into compelling market narratives. This involves cross-functional work to ensure that Bedrock's solutions remain category-defining. You will conduct market research, analyze competitive landscapes, and collaborate with engineering to prioritize feature development based on customer feedback and strategic objectives. Your goal is to position Bedrock Data as the undisputed leader in AI-native data security, crafting messaging that resonates with both technical practitioners and business leaders.

Compensation & Benefits

As an early-stage, well-funded startup, Bedrock Data offers competitive compensation packages designed to attract top-tier talent in the competitive San Francisco Bay Area market. While specific, verified salary bands across all roles are not fully public, industry data and job postings suggest strong alignment with market rates for enterprise security startups.

The compensation philosophy at Bedrock Data is built around rewarding impact and aligning employee incentives with the long-term success of the company. Base salaries are designed to be highly competitive within the cybersecurity and enterprise software sectors, ensuring that the company can attract and retain the specialized talent required to build category-defining technology. For engineering roles, compensation reflects the deep technical expertise required to tackle complex challenges in distributed systems, machine learning, and cloud infrastructure. For sales and go-to-market roles, compensation packages are heavily weighted towards variable performance, offering significant upside for those who can successfully navigate complex enterprise sales cycles and drive revenue growth.

Beyond base salary and variable compensation, equity is a critical component of the total rewards package. As an early-stage company backed by top-tier investors like Greylock, Bedrock Data offers employees the opportunity to share in the significant financial upside of building a successful enterprise software business. Equity grants are designed to foster a sense of ownership and long-term commitment, aligning the interests of employees with those of the founders and investors.

In addition to financial compensation, Bedrock Data provides a comprehensive suite of benefits designed to support the health, well-being, and professional development of its employees. This typically includes top-tier health, dental, and vision insurance, flexible time off policies, and retirement savings plans. The company also recognizes the importance of continuous learning and may offer stipends or reimbursement programs for professional development, certifications, and industry conferences. Given the demanding nature of building a high-growth startup, Bedrock Data strives to create an environment where employees feel supported both personally and professionally, enabling them to do their best work.

The Interview Process

Interviewing at Bedrock Data is designed to assess both deep technical expertise and alignment with the company's agile, startup culture. Candidates can expect a multi-stage process that emphasizes practical problem-solving and strategic thinking.

The process typically begins with an initial screening conversation with a recruiter or hiring manager. This is an opportunity to discuss your background, your interest in the data security space, and your alignment with the company's mission and values. It is also a chance for you to ask questions about the role, the team, and the company's trajectory. If there is a mutual fit, you will advance to the technical or functional assessment stage.

For engineering roles, the technical assessment involves rigorous system design and coding interviews. You will be evaluated on your ability to design scalable, resilient architectures for processing massive volumes of data, as well as your proficiency in relevant programming languages and cloud technologies. The focus is on practical problem-solving rather than theoretical knowledge, and you may be asked to work through complex scenarios related to data ingestion, distributed consensus, or performance optimization. For sales and go-to-market roles, the assessment focuses on your ability to navigate complex enterprise sales cycles, articulate the value proposition of a disruptive technology, and build strategic relationships with senior executives. You may be asked to present a mock pitch, analyze a case study, or discuss your approach to territory planning and account management.

Following the technical or functional assessment, candidates will participate in cross-functional interviews with team members from various departments. This stage is designed to evaluate your ability to collaborate effectively, communicate complex ideas clearly, and thrive in a fast-paced, ambiguous environment. You will be assessed on your cultural fit, your adaptability, and your willingness to take ownership of challenging problems.

Given the company's size and stage, final rounds often include conversations with the founders or executive leadership. This is a critical step in ensuring a strong mutual fit and alignment on the company's long-term vision. The founders are deeply involved in the hiring process, and they are looking for individuals who are not only exceptionally talented but also passionate about building a category-defining company. The interview process is rigorous and demanding, but it is designed to ensure that Bedrock Data hires only the most capable and dedicated individuals.

Why Join / Why Not

Why Join:

If you are passionate about the intersection of Generative AI and cybersecurity, Bedrock Data offers a unique opportunity to build category-defining technology. The company's innovative Metadata Lake approach solves a critical, growing pain point for enterprises. With $25M in Series A funding, backing from top-tier investor Greylock, and a leadership team with a proven track record at major tech companies, Bedrock Data provides a stable yet high-growth environment where your work will have a visible, immediate impact. You will be tackling some of the most complex and pressing challenges in the technology industry, working alongside a team of world-class engineers, security researchers, and business leaders. The potential for professional growth and financial upside is significant, as you will be playing a foundational role in shaping the future of enterprise data security.

Why Not:

As a Series A startup, Bedrock Data is still in a phase of rapid evolution and market discovery. The environment requires a high degree of adaptability, and processes may not be as structured as they are in larger, established corporations. If you prefer a highly predictable day-to-day routine, established corporate hierarchies, or are uncomfortable with the ambiguity that comes with building a new product category, this might not be the right fit for you. Additionally, the roles demand a deep understanding of complex data platforms and security policies, which can be a steep learning curve for those outside the industry. The expectations are exceptionally high, and the pace of execution is relentless. You will be expected to take extreme ownership of your work, navigate complex technical and business challenges, and consistently deliver results in a highly competitive market. If you are not prepared for the intensity and demands of an early-stage startup, Bedrock Data may not be the right environment for you.