Pryon

• Work closely with peers to design & code robust scalable, loosely coupled components and micro-services that integrate with both public and private cloud infrastructure, as well as on-prem applications • Apply architecture and design principles consistently and holistically to enable target end-to-end usage scenarios. • Provide good focus on DevOps and MLOps use-cases and workflows • Build automated pipelines for ML model training, evaluation and deployment

• Design and build production connectors to enterprise systems, handling authentication, sync, pagination, error recovery, and data normalization • Contribute to the evolution of our unified API gateway layer that abstracts source complexity from the rest of the platform • Build and extend systems that enrich content with metadata, permissions, and structural context for downstream consumption • Architect for resilience: design retry strategies, circuit breakers, and graceful degradation for third-party API dependencies • Work with event-driven patterns to enable real-time and incremental synchronization • Collaborate directly with the Ingestion and Retrieval teams to ensure clean handoffs across the pipeline • Take grounded ownership of components — this team needs engineers who see a problem, pick it up, and drive it to resolution

• Design and implement cloud-native architectures for AI/ML applications using Kubernetes (GKE, EKS, AKS) • Architect and maintain CI/CD pipelines using modern GitOps practices with tools like FluxCD and BitBucket • Design and implement observability solutions using Prometheus, Grafana, and other monitoring tools • Create and maintain Infrastructure as Code (IaC) using Terraform • Implement container orchestration strategies using Docker, Kubernetes, and Helm • Design and implement multi-cloud deployment strategies • Establish SLOs/SLIs and implement SRE best practices • Automate operational tasks and create self-healing systems • Mentor team members on DevOps best practices • Collaborate with ML engineers and researchers to optimize model deployment and serving infrastructure • Stay current with emerging technologies and best practices in the DevOps/MLOps space

• Play a pivotal role in driving the program delivery of our enterprise-grade AI/knowledge management platform from strategy to execution • Own all aspects of technical program management to deliver Pryon Platform ensuring delivery is on schedule, within budget, and meets the customer's requirements • Work across engineering, product, infrastructure, and customer teams to ensure that our ingestion, retrieval, inference, and deployment pipelines scale, perform and meet rigorous reliability, security and user-outcome goals • Enable Pryon to bring its Enterprise Memory Layer vision into production at scale

• Design and build pipeline stages for our modern ingestion architecture - from document intake through embedding generation and index writing • Contribute to the design of next-generation pipeline architecture as the system evolves • Improve system stability and scale: identify bottlenecks, reduce failure rates, and build observability into every stage • Work with workflow orchestration tools to manage complex, multi-step document processing with retry logic, error handling, and state management • Handle the realities of document diversity: PDFs, HTML, Office formats, images, structured and semi-structured data - all flowing through the same pipeline • Collaborate with the Connectors team (upstream) and Retrieval team (downstream) to ensure data flows cleanly across system boundaries • Participate in the ongoing migration from legacy systems, balancing new development with operational stability

• Lead technical discovery sessions with federal customers and government stakeholders to scope requirements, define success criteria, and translate mission needs into actionable solution architectures. • Design scalable, secure, and high-performance architectures that align with federal compliance standards, security requirements, and customer-specific needs. • Build and deliver Proof of Concepts (POCs) and Minimum Viable Products (MVPs) to validate technical approaches and demonstrate solution value in government environments. • Own end-to-end technical documentation, including architecture diagrams, technical specifications, integration guides, and deployment runbooks tailored for federal deployments. • Drive technical alignment across sales, engineering, and product teams throughout the solution lifecycle. • Guide solution implementation from initial design through deployment, ensuring smooth handoff to customer success and support teams. • Evaluate and integrate third-party tools, APIs, and platforms into customer solutions to meet functional, non-functional, and security requirements. • Contribute to internal knowledge bases, reference architectures, and reusable solution patterns for federal engagements.

• Deliver proof of value: Design, build, and deliver proof of value through technical integration between Pryon’s platform and partner technologies. • Experimentation: Proactively "sandbox" and test emerging partner technologies to find new ways to enhance Pryon’s core value proposition. • Technical Evangelism: Create reference architectures, technical blog posts, speak at events, and developer documentation to enable partners to build with Pryon. • Collaborate with R&D: Act as a feedback loop between the partner ecosystem and our internal Product/Engineering teams, ensuring our roadmap is informed by the latest industry shifts and partner needs. • Solution Architecting: Work alongside the GTM team to architect technical solutions that leverage partner capabilities and Pryon.

• Manage complex models within the company’s financial model, including monthly and quarterly forecasting, budgeting, and long-range planning delivering accurate and timely projections • Build and own data pipelines and KPI reporting infrastructure across Snowflake, DOMO, Rillet, and Excel • Assist in financial planning processes as the key FP&A partner to our Head of Finance and team leaders • Produce variance analysis with clear, actionable commentary that drives departmental accountability • Own department-level budget vs. actual reporting and lead Monthly Operating Reviews with department heads • Maintain and improve SaaS metrics reporting: ARR, MRR, churn, expansion, renewal rates, and unit economics • Prepare materials for senior leadership, investor relations, and our Board to communicate financial performance • Conduct deep-dive analyses on compute expense, vendor spend, unit economics, and other strategic priorities • Work with departments to ensure data accuracy and reconcile discrepancies; metric definitions and logic stay with Finance leadership • Support annual operating plan development and long-range planning cycles • Coordinate GL bucketing and mapping recommendations with Finance Manager • Aid in Month-End-Close process

• Own the NL2SQL initiative in close partnership with Research, laying the foundation for how structured data is ingested, productized, and scaled across the platform • Ensure core generative and RAG services are portable-ready, scalable, and designed to operate across deployment environments • Partner closely with our orchestration tool to ensure seamless compatibility, and extensibility across agent workflows • Define how we operationalize MCP (Model Context Protocol) to enable reliable, composable agentic workflows • Own the health, reliability, and evolution of our underlying RAG and generative services, including quality, performance, and long-term extensibility • Act as the connective tissue across Research, Platform, and Applications to unblock and accelerate customer-facing AI experiences • Provide clear ownership and direction for platform capabilities that all downstream AI products and customer experiences depend on • Lead agile ceremonies including refinement, roadmap reviews, sprint planning, and stand-ups • Ensure on-time delivery of product features, enhancements and improvements • Define use cases, set requirements and acceptance criteria for features, utilizing an iterative approach to allow for measurement of success and adoption, and prioritization of enhancements • Own your roadmap and set prioritization for feature delivery from technical teams by synthesizing market research, customer and prospect data, customer needs, and internal/external stakeholder expectations • Demonstrate full knowledge of the development process in your area of focus and at times be a key contributor and mindful guide to engineers and scientists on the team • Interact with customers and market thought leaders to develop a deep understanding and define product requirements and best practices for an enterprise business problem • Author product specifications, inclusive of use cases, and activity flow diagrams; identify data sources, analytics, reporting, and integration requirements • Collaborate with engineering, data science, and other support teams such as user experience, QA, and documentation to create exceptional solutions