Senior Applied AI Engineer, AI Platform

Stack

Responsibilities

• ▹Design agents that automate real fund-operations workflows, owning them from prototype through production
• ▹Build the evaluation layer: test cases from real documents, regression suites in CI, human review, clear success criteria
• ▹Own the AI application architecture: orchestration, multi-agent design, tool contracts, memory and context engineering (RAG, MCP)
• ▹Run it in production: versioned, feature-flagged rollout, rate limits, provider fallback, regional failover within EU data residency
• ▹Build the observability to trace a failure across services and turn it into a fix
• ▹Consolidate document parsing/extraction into a platform other teams can consume
• ▹Set patterns other engineers inherit; mentor engineers across teams on agent and LLM practice

Requirements

• ▹5+ years building production software, including at least one agent or LLM-powered capability taken end to end and owned once live
• ▹Real depth in orchestration and context engineering — tool contracts, memory, RAG, multi-agent design — with Mastra, ai-sdk, LangGraph or similar

Soft skills

About the company

bunch is building the backbone of private markets, combining secure data infrastructure, AI-powered workflows and expert fund services in one integrated system. Production AI already runs at bunch: a document extraction pipeline, agent workflows on Mastra, evaluations, and multi-provider fallback within EU data residency.