AI Engineer
Role details
Job location
Tech stack
Job description
We are seeking a highly skilled AI Engineer / AI Platform Engineer to join a forward-thinking Technology & AI organization. This hybrid role sits at the intersection of AI-assisted application development, full-stack engineering, and AI platform/DevOps. You will take AI-generated prototypes and code (from tools like Lovable, Claude, Cursor, etc.) and transform them into secure, scalable, production-grade enterprise applications. You will also own and evolve the underlying AI development platform, build agentic AI systems, refactor/harden AI-generated code, and establish best practices for responsible AI-assisted development. This is a hands-on individual contributor role ideal for someone who thrives on rapidly turning "vibe-coded" AI concepts into reliable, secure, and observable enterprise software while continuously improving the AI development ecosystem itself.
Requirements
- 5+ years of professional full-stack software development experience (4+ years minimum acceptable with strong AI tooling background).
- Strong proficiency in JavaScript/TypeScript, React (or Vue/Angular), and Next.js.
- Backend development experience with Node.js, Python, or Go.
- Hands-on experience with AI-augmented development tools (Claude Code, Cursor, Lovable, GitHub Copilot, etc.) and the ability to review, refactor, and harden AI-generated code.
- Experience building or enhancing agentic AI agents and LLM integrations.
- Solid understanding of PostgreSQL (ideally Supabase + pgvector), relational data modeling, and at least one cloud data platform (Snowflake, BigQuery, etc.).
- Experience with CI/CD pipelines, Git-based workflows, and modern DevOps practices.
- Strong knowledge of OAuth 2.0 / SSO (Microsoft Entra ID preferred), RESTful/GraphQL API design, and application security (OWASP Top 10).
- Familiarity with cloud platforms (GCP, Azure, multi-cloud preferred) and containerization (Docker, Kubernetes). - Direct experience with Supabase, Vercel, Kong API gateway, and Snowflake integrations.
- Exposure to vector databases / pgvector for AI workloads.
- Experience with monitoring tools (Dynatrace, Datadog).
- Knowledge of software supply chain security (Chainguard, SBOM, image signing).
- Background in retail, automotive, or RV/dealership technology systems.
- Experience building MCP servers or advanced LLM tool-use integrations.
- Deep expertise in Kubernetes, service mesh, or advanced CI/CD architecture.
Benefits & conditions
$70 - $85 / hour