Airbyte•29 days ago
AI Platform Engineer
Recruiter Fit Breakdown & Candid Summary
1
This role is for a seasoned backend engineer to build the orchestration layer that connects LLMs to enterprise systems.
2
Ideal candidates have deep experience in distributed systems and have moved beyond simple RAG to building agentic workflows.
3
This is a high-ambiguity, early-stage product role; it is not suitable for engineers who prefer strictly defined requirements or purely research-focused AI work.
4
Expect to balance rapid prototyping with the rigor required for production-grade enterprise data infrastructure.
Role Responsibilities
- 1Design and implement the orchestration layer for natural-language intent execution.
- 2Build systems for entity resolution, context assembly, and evidence retrieval.
- 3Develop reusable Skills that encapsulate business workflows and domain expertise.
- 4Build routing systems to coordinate connectors, tools, and multiple language models.
- 5Develop evaluation frameworks to ensure reasoning quality and traceability.
- 6Implement permission models and action policies for secure agent execution.
Skills Matrix
Must-Have Skills
Distributed Systems
Backend Engineering
LLM(Large Language Models)
AI Agents
RAG(Retrieval-Augmented Generation)
System Design
Orchestration Systems(workflow engines)
Nice-to-Have Skills
LangGraph
Temporal
MCP(Model Context Protocol)
Vector Search
Knowledge Graphs
Kafka
Apache Iceberg(Iceberg)
Postgres
Spark
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