Software Engineer – AI Agents
AI summary of the role
Design and build agentic features (document understanding, advanced RAG, customer support automation) and the Friendli Agent API.
What you’ll do
- Design, build, and maintain agent APIs and applications for document understanding and other high-value features
- Evaluate and integrate open-source models to power production-ready agent features
- Develop reference agent applications to showcase workflows and accelerate customer adoption
- Collaborate with backend and infrastructure teams to integrate agents with deployment, orchestration, and monitoring systems
What you’ll bring
- 3+ years of experience in software engineering, preferably in backend, ML systems, or API development
- Strong programming skills in Python; experience with various Python frameworks
- Solid understanding of LLM workflows, agent patterns, or tool invocation systems
- Experience designing and delivering production APIs
Technologies
Python · HuggingFace · LangChain · LlamaIndex · Kubernetes · RAG · OCR · LLM · API development · container orchestration
About FriendliAI
Generative AI inference platform selling fast, cost-optimized LLM/agent serving (managed endpoints + on-prem engine) to enterprises.
Seed · 50–200 people
Source and classification
Production engineering · Evidence for this classification:
About the Job We’re seeking an Agent Engineer to design and build agentic features in our platform, including document understanding, advanced RAG, and customer support automation. In this role, you will develop not only the agent components themselves, but also the Friendli Agent API, which serves as the core developer interface for building and extending agent applications. You will also build agent applications as production-ready examples of how agents can solve real-world problems. These applications will be primarily written in Python and will serve as reference implementations for our customers and community. We are looking for a hands-on engineer who is passionate about building agent systems and making AI easy for developers to adopt. The ideal candidate is comfortable creating agent applications that showcase what is possible, is curious about and experienced withHow jobs are selected
Employer postings · Data from · Sources