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Senior AI Engineer
Skills
AdoptionAmazon Web ServicesBedrockBusinessCollaborative EnvironmentConnectorsContext
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
