AI Automation Engineer & Architect - Remote Full Time
Indexed description
This Role Sits At The Intersection Of
- LLM systems (RAG, agents, orchestration)
- Cloud-native multi-tenant SaaS architecture
- Event-driven backend engineering
- Intelligent workflow automation
- Production reliability & observability
What You’ll Own
AI Systems & RAG Architecture
- Design and deploy production-grade RAG pipelines using Vertex AI, Gemini, OpenAI, or Anthropic
- Build embedding and ingestion pipelines for structured and unstructured business data
- Implement vector search using Pinecone, Weaviate, ChromaDB, or pgvector
- Architect context management strategies balancing latency, cost, and reliability
- Design multi-step agentic workflows using LangChain, LangGraph, or LlamaIndex
- Build state machines that reason, retain context, and execute business actions
- Integrate AI agents with systems like Greenhouse, HubSpot, QuickBooks, and internal services
- Implement guardrails, evaluation pipelines, and hallucination mitigation strategies
- Build scalable backend services using Python (FastAPI preferred) and TypeScript/Node.js
- Design event-driven systems (SQS/SNS, Pub/Sub, retries, DLQs, idempotency patterns)
- Architect secure, multi-tenant SaaS infrastructure across AWS and GCP
- Manage infrastructure as code using Terraform
- Own CI/CD pipelines with GitHub Actions
- Implement observability, logging, and model monitoring
- Partner with product and leadership to turn operational problems into AI-driven workflows
- Define measurable success criteria for automation systems
- Communicate tradeoffs clearly (cost, token usage, reliability, latency)
- Have 8+ years in software engineering
- Have 3+ years deploying AI/ML systems into production
- Have built real RAG pipelines (not tutorials)
- Have implemented LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex)
- Understand vector databases deeply
- Have strong Python and backend architecture experience
- Have worked in multi-tenant SaaS or ERP-like systems
- Have built event-driven architectures
- Have owned CI/CD and production reliability
- Think in systems and workflows — not just models
- Python (AI orchestration, data pipelines, backend services)
- TypeScript / Node.js (API services and integrations)
- LLM providers (Gemini preferred, OpenAI/Anthropic acceptable)
- RAG frameworks and retrieval optimization
- Vector databases (Pinecone, Weaviate, ChromaDB, pgvector)
- PostgreSQL (multi-tenant schemas, migrations)
- AWS (IAM, VPC, ECS/EKS, Lambda, SQS/SNS, RDS, Secrets)
- GCP (Vertex AI, Cloud Run, Pub/Sub)
- Terraform
- GitHub Actions CI/CD
- Event-driven architecture patterns
- Experience embedding AI into SaaS products
- LLM evaluation & monitoring pipelines
- Guardrails and reliability strategies
- Cost optimization for token-heavy workloads
- Experience integrating third-party SaaS tools via OAuth & webhooks
- Frontend familiarity (React/Next.js) for AI UX integration
- Ship at least one production-grade RAG workflow
- Deploy a multi-step agentic workflow tied to a real business function
- Establish monitoring for latency, cost, and reliability
- Contribute to scalable AI architecture standards across the platform
Bold Business recruiters always use a “@boldbusiness.com” email address and/or from our Applicant Tracking System, Greenhouse. Any variation of this email domain should be considered suspicious. Additionally, Bold Business recruiters and authorized representatives will never request sensitive information in email or via text.
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