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Senior Engineer, Knowledge Systems

Builds foundational backend infrastructure for structured knowledge storage, headless CMS, APIs, and AI integrations. Partners with design/product teams; requires 7+ years experience in APIs, content systems, search, and leading complex implementations.

168k – 235kNew York, NYBackend EngineeringOnsite7+ YOE

About the role

Responsibilities

  • Design and build foundational infrastructure for structured knowledge storage, versioning, and retrieval
  • Partner with Content Design, Product, and Engineering to translate knowledge architecture into technical systems
  • Stand up and configure headless CMS implementing knowledge operating model
  • Develop APIs and services exposing structured knowledge to internal tools, AI assistants, and products
  • Build integrations between knowledge systems and AI tooling, including RAG architectures
  • Prototype with Git-based content, markdown workflows, and developer-friendly authoring
  • Collaborate to identify opportunities for structured knowledge in product workflows and AI
  • Evaluate and recommend technologies for knowledge storage and delivery
  • Establish patterns for content versioning, governance, and metadata management
  • Support internal enablement needs like SOPs, policies, decision trees
  • Iterate on architecture as systems mature

Technologies Used

Core stack:

  • Golang, Ruby on Rails, JavaScript
  • MySQL, Redis, ElasticSearch
  • Kafka, Temporal
  • AWS infrastructure
  • Git, GitHub, Docker, Kubernetes, Terraform, CircleCI, DataDog

Helpful experience:

  • Headless CMS (Contentful, Sanity, Strapi)
  • Git-based content workflows, markdown repositories
  • Knowledge retrieval systems, RAG architectures
  • Search and indexing systems
  • API-driven content platforms

Qualifications

  • 7+ years as software engineer building production systems
  • Strong experience designing APIs and backend services for multiple consumers
  • Experience with structured content systems, CMS, or knowledge management infrastructure
  • Leading technical implementation of complex systems, coordinating engineers
  • Designing/integrating information retrieval or search systems
  • Familiarity with AI tooling, integrating LLM workflows with structured knowledge
  • Designing systems modeling entity/policy relationships
  • Strong collaboration with non-engineering partners
  • Operate autonomously in ambiguous spaces

Skills

GoRuby on RailsJavaScriptMySQLRedisElasticsearchKafkaTemporalAWSKubernetesDockerTerraformHeadless CmsRAGContentful

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