Overview
In MPB’s AI Automation Hub, you will build production-ready, agentic AI systems that improve daily workflows. You’ll work alongside a small, peer-led team to move ideas from concept to usable tools, shaping how we evaluate AI outputs and select models. The role blends hands-on engineering with cross-functional collaboration to deliver high-value AI use cases. You’ll help scale our hub across markets and foster a culture of learning and responsible AI deployment.
Responsibilities
- Design and ship production-ready AI systems including agents, retrieval pipelines and automations
- Prototype quickly with working demos; align implementations with the agentic reference architecture
- Collaborate with AI Product Manager and AI Scientist to prioritize backlog and ensure value
- Evaluate LLM outputs and select appropriate models to balance budget and impact
- Coach and influence teams across MPB experimenting with AI
- Identify and communicate which AI opportunities are worth acting on and track frontier developments
Key requirements
- Strong software engineering background with production-distributed systems
- Hands-on experience with LLM orchestration, agent frameworks and RAG
- Experience with low-code automation tools (n8n)
- Proficient in Python or Node.js
- Experience with cloud-native architecture (GCP or AWS), API management and robust backend pipelines
- Structured, pragmatic approach to debugging non-deterministic systems
- Ability to explain complex ideas clearly to a non-technical audience
- Degree in Computer Science, Engineering or related field (or equivalent experience)
- Experience coaching or influencing teams without formal authority
- Track record of turning emerging AI tooling into practical opportunities
- Clear communication
- Cross-functional collaboration
- Mentoring or coaching
- LLM orchestration
- Agent frameworks
- RAG
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