Description
Negotiating a million-dollar enterprise contract is a very different problem from answering questions in a chatbot. An AI system has to understand pricing, commercial terms, risk, timing, supplier relationships, internal objectives, and the consequences of making the wrong recommendation.
That is the environment behind Monq's Applied AI Engineer position. The company is building autonomous negotiation agents for enterprise procurement teams, and this engineer will help turn large language models into systems capable of reasoning through high-value commercial negotiations.
Work spans agentic LLM workflows for contract analysis, vendor research, negotiation planning, and decision support. Agents may be specialized for areas such as software, professional services, logistics, or capital equipment, while orchestration logic coordinates them around broader procurement objectives.
Multi-dimensional optimization is an important part of the product. The system cannot optimize only for the lowest price; it needs to consider payment terms, risk, delivery timelines, contractual obligations, supplier relationships, and other constraints that may matter more than a small pricing improvement.
The engineering scope also includes multi-agent collaboration, LLM evaluation, guardrails, monitoring, explainability, and security. Because these systems are used in enterprise negotiations, behavioral consistency and auditability matter considerably more than they would in a casual consumer AI experience.
Integration work connects the agents to procurement platforms such as SAP, Oracle, Coupa, and GEP. Engineers may also contribute to real-time dashboards and control interfaces that allow procurement professionals to supervise or interact with autonomous workflows rather than giving an agent unrestricted authority.
Monq is looking for strong Python experience and practical knowledge of modern LLM systems. Production deployment experience with evaluation, monitoring, and guardrails is particularly useful, along with a Master's or PhD in machine learning, computer science, or another quantitative field.
This position is well suited to someone interested in applied AI where research ideas have to survive enterprise constraints, real customer workflows, and high-value business decisions rather than remaining experimental prototypes.
Curated opportunity. Please verify details and apply via the original link below. No Signals are required for this project/job.
https://careers.monq.io/jobs/7937921-applied-ai-engineer