AI Automation Engineer & Architect - Remote Full Time
Summary
Architect and build production-grade AI systems using LLMs, RAG, and agentic workflows on cloud-native infrastructure for a global BPO firm.
- Event-driven backend engineering
- Intelligent workflow automation
About The Role
We’re hiring an AI Automation Architect (LLM & Cloud) to architect and build the core intelligence layer behind Bold Amplify™. You will design and ship real AI systems used by real customers — not prototypes, not experiments.
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
If you’ve built production RAG pipelines, deployed LLM-backed services, and care about clean architecture and measurable impact — this role is for you.
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
Agentic Workflows & Orchestration
- 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
Backend & Cloud Architecture
- 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
Business Translation
- 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)
Who We’re Looking For
- Have 8+ years in software engineering
- Have 3+ years deploying AI/ML systems into productionli>
Required Technical Experience
- 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
Bonus
- 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
What Success Looks Like
- 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
About Bold Business
Bold Business is a US-based global business process outsourcing (BPO) firm with over 25 years of experience and $7B+ in client engagements. We help fast-growing companies scale through smart talent strategies, automation, and technology-driven solutions.