Senior Software Engineer, Backend

About Doowii Doowii is building a conversational analytics platform for education. We enable non-technical users to query complex datasets using natural language, accelerating decision making, data exploration, and intervention planning. Doowii sits at the intersection of data infrastructure, AI, and education. About the Role This individual contributor role is a technical leadership opportunity focused on building the core systems that power Doowii. Applicants must demonstrate technical mastery, architectural skills, mentoring abilities, and independence. You’ll be tackling opportunities and projects core to the Doowii interface and backend: define architecture lead development projects and make critical technical decisions ensure the system scales across customers, data, and use cases identify opportunities to elevate user experience What You’ll Work On Doowii engineering is critical in the end-to-end development of the Doowii platform, applications, and systems, from designing the user interface to managing our systems and infrastructure.  Backend Systems Design and build scalable backend services, APIs, and platform capabilities that power the Doowii application Lead development of high-impact, cross-cutting technical initiatives across application, data, and infrastructure layers Design and maintain patterns for integrations, data modeling, reliability, observability, and performance Own system performance, monitoring, troubleshooting, and operational excellence Improve deployment, testing, and CI/CD workflows to increase engineering velocity and reliability Partner with product, frontend, and AI engineers to deliver AI-powered product capabilities Data & Analytics Infrastructure Guide how data is structured, accessed, transformed, and optimized across the platform Influence architecture decisions related to analytics infrastructure, AI systems, and large-scale data processing Design and maintain analytical data models to support reporting, natural language querying, and customer-facing analytics Optimize storage, compute, and query performance across operational and analytical workloads Develop and maintain ingestion and transformation pipelines across multiple systems and data sources Support schema evolution, data quality, lineage, and governance requirements as the platform scales Integrations & AI Systems Build and maintain integrations with customer systems, third-party APIs, identity providers, and external data platforms Design services that support AI-powered experiences including retrieval systems, semantic search, vector-based workflows, and LLM-driven product features Collaborate with AI engineers to operationalize models, evaluation frameworks, and production AI workflows Team Impact Mentor engineers and elevate engineering standards across architecture, reliability, testing, and operational excellence Provide technical leadership on complex engineering initiatives Partner closely with product and leadership teams to align technical investments with business objectives Contribute to engineering culture through documentation, design reviews, and knowledge sharing Requirements BS in Computer Science, Computer Engineering, Software Engineering, or related field (or equivalent practical experience) 5+ years of software engineering experience, primarily focused on backend systems Strong proficiency in Python and experience building production backend services and APIs Deep experience with SQL, relational databases, and data-intensive applications Experience designing and operating distributed systems in production environments Experience with cloud infrastructure (AWS, GCP, or Azure) and modern deployment workflows Experience designing and maintaining APIs, integrations, authentication systems, and data synchronization workflows Experience with observability, monitoring, incident response, and operational reliability practices Experience with schema evolution, change data capture (CDC), event-driven architectures, or high-throughput data processing systems Bias toward automation, clear documentation, maintainable systems, and rapid iteration in a startup environment Experience building, integrating, or operationalizing AI/LLM-powered applications, workflows, or services Bonus points if you have: Master's degree in Computer Science, Computer Engineering, Data Engineering, Machine Learning, or a related field Experience building analytics platforms, data products, BI systems, or customer-facing reporting solutions Experience working with modern data infrastructure and orchestration technologies Hands-on with at least two of: Kafka or Pub/Sub, Apache NiFi, Airflow, Mage.AI, Beam, Spark, Flink, dbt, Iceberg/ClickHouse Experience implementing retrieval-augmented generation (RAG), semantic search, vector databases, or agent-based systems Experience supporting enterprise-scale integrations, SSO (OAuth/SAML), or customer onboarding workflows Experience optimizing large-scale data processing, storage, and query performance