Clear Fracture LLC

Role Description We are looking for a Technical Growth Lead who operates as a hands-on practitioner first, with the credibility to speak directly to data engineering teams and buyers. You will play a key role in building and running the first version of our repeatable demand/marketing engine — shipping campaigns, managing paid tests, building target-account lists, running webinars, and reporting on marketing performance every week. In addition to executing campaigns, you will help refine demos, publish technical content, and identify the markets where the platform has the strongest pull. This includes designing the messaging, assets, and workflows that turn data engineering practitioners into qualified targets. Qualifications - 2+ years of prior experience as a data engineer, analytics engineer, or technical data practitioner. - 2+ years of experience building demos and proof-led content. - Due to the nature of the work, U.S. Citizenship and the ability to obtain a Secret Clearance are required. - Ability to speak credibly to data engineering teams and buyers about their language, workflows, and pain points — including pipelines, data quality, data contracts, orchestration, governance, and AI-assisted engineering. - Strong written communication skills suitable for technical practitioner audiences. - Comfort owning weekly funnel reporting and adjusting tactics based on signal. Requirements - Hands-on experience shipping marketing campaigns, including landing pages, email nurture, paid tests, and retargeting. - Experience managing marketing operations: website goals, CRM source fields, UTMs, and weekly scorecards. - Experience running webinars, live teardowns, or practitioner-led events. - Experience marketing developer tools, data infrastructure, or AI/ML platforms. - Experience operating as a hands-on growth lead at an early-stage company. - Familiarity with paid platforms (LinkedIn, Google Search, retargeting networks) and marketing automation / lifecycle systems. - Active security clearance. Benefits - Be part of a dynamic and rapidly growing team at the forefront of AI and data integration. - Opportunity to work on innovative multi-agent solutions for critical missions. - Make a significant impact on how organizations leverage data for decision-making and operational efficiency. - Collaborative and supportive work environment focused on innovation and customer success.

Role Description Clear Fracture is building AI-driven data integration systems that enable organizations to connect, transform, and reason over complex data using agentic workflows. Our platform operates across cloud and on-prem environments and is designed to support multi-tenant, production-scale use cases. We are looking for a Data Engineer who operates as a software engineer first, with strong experience in data modeling and data systems. You will play a key role in building the core data layer that powers our agentic platform—designing schemas, implementing data services, and enabling reliable, scalable data flows. In addition to building core data infrastructure, you will also develop real use cases on the platform itself, helping shape how users interact with data. This includes designing data interfaces, abstractions, and tooling that make it easier to understand, model, and work with data across the system. This is not a traditional ETL-only role. You will write production code, design systems, and help define how data is represented, accessed, and understood across the platform. Qualifications - Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience. - 6+ years of professional experience in software engineering and/or data engineering roles. - Due to the nature of the work, U.S. Citizenship and the ability to obtain a Secret Clearance are required. - Strong programming skills in Python (or similar backend language). - Experience designing and implementing data models for production systems, with advanced knowledge of dimensional modeling topics like slowly changing dimensions and entity relationship diagrams. - Proficiency in SQL and experience with relational databases (e.g., PostgreSQL). - Experience building backend services or APIs that interact with data systems. - Experience designing and operating data pipelines (ETL/ELT). - Familiarity with NoSQL databases and different data storage paradigms. - Experience working with large datasets and performance optimization. - Experience with Docker and containerized development workflows. - Familiarity with Kubernetes-based environments. - Strong understanding of software engineering fundamentals (testing, version control, system design). Requirements - Design and implement logical and physical data models for complex, evolving datasets. - Define schemas and access patterns that support multi-tenant usage and application-level workflows. - Balance normalization, performance, and flexibility across different storage systems. - Partner with product and engineering teams to translate requirements into scalable data designs. - Develop real-world data use cases on top of the platform to validate and extend its capabilities. - Design and build data interfaces and abstractions that help users understand and work with data. - Contribute to systems such as data glossaries, semantic layers, and metadata and schema discovery tools. - Help define how users explore, model, and interact with data within the platform. - Translate complex data structures into intuitive, usable representations. - Build backend services and APIs that expose and operate on data models. - Implement data access layers that are reliable, maintainable, and performant. - Contribute to core application architecture where data and services intersect. - Write clean, testable, production-grade code. - Design and implement pipelines for ingesting, transforming, and validating data. - Support both batch and near-real-time processing workflows. - Build systems that handle structured, semi-structured, and unstructured data. - Enable data flows that support AI-driven and agent-based workflows. - Work with embeddings, context retrieval, and data representations used in modern AI systems. - Help design systems that make data accessible and useful for autonomous agents. - Implement validation, monitoring, and testing for data systems. - Ensure correctness, consistency, and observability of data pipelines and services. - Diagnose and resolve data-related issues in production environments. Benefits - Engineering mindset: You approach data systems as software systems, not just pipelines. - Data intuition: You understand how to model real-world complexity into clear, usable structures. - Product thinking: You care about how users interact with and understand data, not just how it is stored. - Systems thinking: You see how data flows through services, APIs, and AI systems. - Ownership: You take responsibility for the reliability and usability of what you build. - Pragmatism: You balance ideal design with real-world constraints. - Collaboration: You work effectively across engineering disciplines.

Role Description We are seeking a backend focused Senior Software Engineer to design and build the authorization and identity systems embedded directly within our product. This is a hands-on engineering role focused on implementing fine-grained access control, authentication flows, and tenant-aware security mechanisms across our platform. You won't just be managing an identity provider; you’ll be designing and coding the high-performance authorization middleware and SDKs that allow autonomous agents to navigate sensitive data pipelines securely. If you enjoy solving complex distributed systems problems where 'standard' cloud-based solutions don't work, this is your role. You will work closely with backend, platform, and DevOps engineers to integrate authorization into core application workflows, APIs, and agent systems. This role is ideal for engineers who enjoy building security-critical systems in production code, not just configuring or operating infrastructure. Note: This is not a DevOps or infrastructure security role. It focuses on building application-layer authorization and identity systems. Key Responsibilities - Authorization Systems: Design and implement fine-grained authorization systems within the product, including role-based and policy-based access control models for users, organizations, APIs, and agent workflows. - Application Integration: Write production-level backend code to enforce authorization across APIs, services, and agent execution paths. Partner with other engineers to embed access control directly into core product functionality. - Identity & Authentication: Implement authentication flows and integrate with enterprise identity providers (OAuth2, OIDC, SAML, Active Directory), ensuring seamless and secure user and service authentication. - Multi-Tenant Design: Design and enforce tenant-aware access control and isolation across application services, data layers, and compute workloads. - Security Architecture (Application Layer): Contribute to the design of authorization and identity architecture, including policy models, enforcement patterns, and system boundaries. - Secure System Design: Participate in threat modeling and design reviews, with a focus on authorization boundaries, privilege escalation risks, and least-privilege enforcement. - Agentic Security: Defining and monitoring operational constraints to mitigate the risk of prompt injection or goal-misalignment. - Distributed Systems Integration: Design authorization approaches that function reliably across distributed systems, including cloud-connected and air-gapped environments. - Developer Experience: Create clear abstractions, APIs, and documentation that make it easy for other engineers to correctly implement and extend authorization logic. Qualifications - 4+ years of experience building authorization, identity, or authentication systems in application code. - Strong backend software engineering experience (e.g., Python, Go, Java), including: - Designing APIs - Implementing authentication flows - Enforcing authorization in service logic - Deep understanding of: - RBAC, ABAC, and/or policy-based access control models - OAuth2, OpenID Connect (OIDC), SAML, and enterprise SSO - Experience designing or implementing fine-grained permissions in complex or distributed systems. - Experience working on multi-tenant applications or systems with strong isolation requirements. - Familiarity with threat modeling and secure system design, especially around access control and trust boundaries. - Comfortable working in a collaborative engineering environment and integrating security into shared codebases. - Experience building or deploying systems in cloud environments. (AWS, Azure, or GCP) - Strong communication skills and ability to explain technical concepts clearly. - Bachelor’s degree in Computer Science or equivalent practical experience. - Due to the nature of the work, U.S. Citizenship and the ability to obtain a Secret Clearance are required. Desired Qualifications (Plus Factors) - Experience building or integrating authorization frameworks or policy engines. (e.g., OPA, Cedar, Zanzibar-inspired systems) - Experience designing authorization for dynamic systems. (e.g., agent-based systems, workflow engines, or plugin architectures) - Experience implementing relationship-based or context-aware access control models. - Experience supporting on-prem or air-gapped deployments. - Experience with enterprise identity integrations in complex environments. - Experience working in high-assurance or regulated environments. - Familiarity with secrets management tools. (e.g., Vault) - Exposure to compliance frameworks. (SOC2, FedRAMP, etc.) - Advanced degree in Computer Science or related field. - Active security clearance. Benefits - Be part of a dynamic and rapidly growing team at the forefront of AI and data integration. - Build core authorization systems for a next-generation AI platform. - Work on technically challenging problems at the intersection of distributed systems, security, and agentic workflows. - Have direct ownership over how access control is designed and implemented across the platform. - Collaborate with a highly technical team building complex, high-impact systems. - Foster an environment of growth and development, with an emphasis on opportunity, recognition, and work-life balance.