Sr. Software Engineer, Developer Experience and Productivity Engineering -10451

Design and implement AI and MCP tools architecture, focusing on scalability and maintainability

Develop integration mechanisms that allow our AI platform to connect with MCP systems while providing a unified interface

Create and enhance AWS RAG systems to incorporate Coupa's institutional knowledge into AI decision-making

Build secure connectors to internal documentation, systems, and data sources

Implement domain-specific tools that understand Coupa's unique operational environment

Optimise tool selection and execution to ensure efficient LLM interactions

Collaborate with product managers to prioritise and implement features that deliver business value

Mentor junior engineers and contribute to engineering best practices

Building a scalable, domain-based hierarchical structure for our AI platforms

Creating specialised tools that understand Coupa's unique environment and operational practices

Implementing secure knowledge integration with AWS RAG and Knowledge Bases

Designing systems that maintain tool manageability while expanding capabilities

Developing contextual awareness capabilities that leverage Coupa's institutional knowledge

Opportunity to work at the cutting edge of AI integration and orchestration

Solve complex technical challenges that have direct business impact

Collaborate with a talented team passionate about AI innovation

Build systems that transform how businesses leverage AI for operational efficiency

Contribute to an architecture that scales intelligently as capabilities grow

Work with the latest LLM technologies and help shape their application in enterprise environments

5+ years of professional software engineering experience

Strong proficiency in Python and RESTful API development

Experience building and deploying cloud-native applications, preferably on AWS

Understanding of AI/ML concepts, particularly in the context of LLMs and their applications

Solid knowledge of software design patterns, system architecture, and performance optimisation

Experience with integration of multiple complex systems and APIs

Strong problem-solving skills and attention to detail

Excellent communication skills and ability to explain complex technical concepts clearly

Experience with AI orchestration platforms or building tools for LLMs

Knowledge of vector databases, embeddings, and RAG systems

Familiarity with monitoring tools like New Relic, observability patterns, and SRE practices

Experience with Jira, Confluence, GitHub, or other DevOps tools and their APIs

Understanding of security best practices for AI systems and data access

Previous work with domain-driven design and microservices architecture

Contributions to open-source projects or developer tools