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Senior AI Engineer

Skills
AdoptionAmazon Web ServicesBedrockBusinessCollaborative EnvironmentConnectorsContext
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • 4+ years of software engineering experience
  • Proven experience building AI tooling used by others in a commercial environment
  • Strong full-stack skills in TypeScript
  • Frontend skills with Next.js or React
  • Knowledge of MCP Model Context Protocol
  • Experience shipping containerised software to Kubernetes
  • Comfortable working with LLMs embeddings and AI application patterns
  • Experience designing and building API integrations
  • Self-starter who takes ownership end-to-end
  • Motivated by impact

Nice to have

  • Curious
  • Ownership mindset
  • Impact driven
  • Collaborative
  • Resourceful

Day to day

  • Build AI tooling on top of the cloud closing agent pronto and improve internal engineering workflows
  • Create connectors and integrations that expose company data to AI systems including Google Workspace Slack Jira GitHub Snowflake and Confluence
  • Develop knowledge base pipelines MCP integrations and API connections while ensuring security and data governance requirements are met
  • Enable internal teams to build AI-powered data sources automated workflows and internal tools using rapid app builder tools
  • Work with PMs and engineering leads to ship quickly measure impact and iterate based on adoption time saved and errors reduced

Hiring process

  • Screening call with Hiring Manager
  • Take-home task
  • Technical interview based on the task
  • Interview with Product Manager
  • Final interview with Hiring Manager