About The Position

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, and identify opportunities to elevate user experience. 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.

Requirements

  • BS in computer engineering (or similar field with 10+ years of experience)
  • 5+ years of full-stack experience
  • Strong full-stack expertise, covering frontend (JavaScript/TypeScript, modern frameworks) and backend skills (Python preferred)
  • Deep experience with cloud infrastructure
  • Experience with APIs and SQL
  • Experience with schema evolution, CDC, and high-throughput streaming
  • Bias for automation, clear documentation, and fast iteration in a startup environment
  • Experience with AI model/agent development and LLM evaluation

Nice To Haves

  • Masters in computer engineering
  • Experience building data-heavy platforms or analytics products
  • Strong product intuition and UX thinking
  • Experience with performance optimization
  • Hands-on with at least two of: Kafka or Pub/Sub, Apache NiFi, Airflow, Mage.AI, Beam, Spark, Flink, dbt, Iceberg/ClickHouse

Responsibilities

  • Lead development of high-impact, cross-cutting features
  • Resolve ambiguous problems with incomplete information
  • Partner with ML, product, and frontend engineers to ship AI-driven features (LLM text-to-SQL, embeddings, feature stores, LLM-driven data modeling)
  • Design scalable systems across application, data, and infrastructure layers
  • Define patterns for integrations, data modeling, and performance
  • Own system performance, observability, and reliability
  • Improve deployment and operational workflows
  • Guide how we structure, access, and optimize data
  • Influence decisions around analytics infrastructure and AI integration
  • Design and maintain data models (star, wide-table, or Iceberg-native) to support real-time and batch analytics
  • Optimize storage + query performance
  • Develop and maintain ingestion pipelines (NiFi 2.0 → Kafka → Iceberg → BigQuery) end-to-end
  • Mentor engineers and raise engineering standards
  • Act as a technical partner to Doowii’s product and leadership teams
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