• 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 build production-grade LLM integrations and services in C#/.NET • Develop secure, scalable, high-performance backend systems • Manage prompt pipelines, streaming and parallelised execution • Solve complex challenges related to system integration, stability and performance • Collaborate closely with Product Managers and Designers on new features • Contribute to architecture, system design and refactoring • Experiment, prototype and explore new AI capabilities • Deliver customer value in small, continuous increments • Mentor and support other engineers within the team

• Utilize your extensive programming experience, with a minimum of four years in a professional setting, preferably within a small team. • Demonstrate flexibility by not adhering strictly to a specific programming language, editor, or libraries. Embrace a holistic approach to software development by seamlessly transitioning between frontend, backend, and infrastructure tasks. • Be the go-to person for technical guidance and architectural decisions within the team. Assume a leadership role when systems face challenges and contribute to effective problem resolution. • Apply a discerning eye to identify and address premature over-engineering, ensuring projects progress efficiently. Recognize the long-term consequences of programming choices and navigate trade-offs to optimize solutions. • Understand that code serves the business/customer problem it aims to solve. Thrive in making informed trade-offs that efficiently address these problems.