AI Full Stack Engineer
New
G
GigaBrandsAmazon brand management
Austin, Texas, United States. Brazil. ColombiaFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 3+ years
- Required Skills
- Node.jsPostgreSQLOAuthTypeScriptREST APIReactLinuxLLM
Requirements
- Production LLM experience (Claude/OpenAI in real systems)
- RAG system experience (embeddings, retrieval, chunking, context handling)
- 3+ years TypeScript / Node.js
- Strong React skills
- PostgreSQL (queries, migrations, indexing)
- API integrations (REST, OAuth, webhooks)
- Linux server experience (SSH, logs, debugging, deployments)
- Experience with multi-agent LLM systems (strong plus)
- Anthropic Claude expertise (strong plus)
- Vector search / embeddings (strong plus)
- Slack API experience (strong plus)
- Ad platform APIs (Meta, Google, LinkedIn) (strong plus)
- LLM observability (cost, tracing, monitoring) (strong plus)
- Amazon / eCommerce experience (strong plus)
- AI-assisted dev tools (Cursor, Claude Code, etc.) (strong plus)
Responsibilities
- Build AI pipelines for client performance insights
- Improve RAG retrieval quality
- Add tool use for real-time data in LLM pipelines
- Debug classification errors in AI systems
- Optimize LLM costs and performance
- Build dashboards for AI metrics and usage
- Add observability to pipelines
- Expand content quality systems
- Classify inbound messages by category, intent, urgency, and tone
- Generate contextual responses using enrichment data
- Implement human approval gates
- Transform raw enrichment data into structured pre-call briefs
- Generate: background, pain hypotheses, talking points, rapport hooks
- Develop vector database with embeddings, markdown-aware chunking, async ingestion workers, and semantic search API
- Process RSS feeds, social media, video platforms, and search trends for trend intelligence
- Generate reports, forecasts, and content drafts autonomously
- Develop multi-agent system (outline → audit → generate) for content quality
- Implement binary quality gates (PASS/FAIL with citations) for content
- Enrich leads with product data and market insights
- Implement AI scoring and qualification grading for leads
- Automate audit reports
- Manage Slack operations, scheduling workflows, email triage and follow-ups as an AI Executive Assistant
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