Full Stack Automation Engineer
Tasks
- Add observability and tracing
- Add tool use function calling for LLMs
- Automate scheduling workflows
- Build AI communication pipelines
- Build AI scoring and qualification systems
- Build async ingestion workers
- Build dashboards for AI metrics
- Build semantic search APIs
- Classify inbound messages
- Debug classification errors and improve accuracy
- Enrich leads with product data
- Expand content quality systems to new formats
- Generate automated audit reports
- Generate contextual responses
- Generate reports and forecasts
- Generate sales talking points
- Implement human approval gates
- Implement markdown aware chunking
- Implement multi agent content quality pipeline
- Implement reranking and hybrid search
- Improve RAG retrieval quality
- Integrate Slack operations
- Maintain PASS FAIL quality gates with citations
- Maintain vector database with embeddings
- Optimize LLM costs latency and performance
- Process RSS feeds and social trends
- Run scheduled autonomous jobs
- Support multiple content formats
- Transform enrichment data into structured briefs
- Triage and respond to email
Perks/Benefits
Skills/Tech-stack
AWS Lambda | Chunking | Docker | Embeddings | Function Calling | Hybrid search | LLM Observability | Linux | Monitoring | Node.js | OAuth | PostgreSQL | Query Optimization | RAG | REST API | React | Reranking | Semantic Search | Slack API | Terraform | Tool use | Tracing | TypeScript | Vector Database | Webhooks
Education
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