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Salary
≈ $128k – $252k per year (Estimated)
Location
Hybrid (San Francisco, United States)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Apr 15, 2026. FriendliAI scores C on the Alion truth index.

Overview
Company
Impact
Profile match
FriendliAI is the fastest inference cloud for agents, built to run frontier open-weight models in production at scale.
Backed by Sierra Ventures

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 with open-source models, and enjoys turning them into reliable, high-impact features.

Key Responsibilities

  • Design, build, and maintain agent APIs and applications that deliver document understanding and other high-value features

  • Evaluate and integrate open-source models to power production-ready agent features where possible

  • 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

  • Ensure APIs are robust, developer-friendly, and enterprise-ready through strong design principles and documentation

  • Continuously improve the reliability, scalability, and performance of agent features in production

Qualifications

  • 3+ years of experience in software engineering, preferably in backend, ML systems, or API development

  • Bachelor’s or Master's degree in Computer Science, Computer Engineering, or equivalent

  • 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

  • Familiarity with open-source LLMs and multimodal models (HuggingFace, LangChain, LlamaIndex, etc.)

  • Strong foundations in cloud-native development

Preferred Experience

  • Experience with document understanding pipelines (e.g., OCR, RAG, summarization, structured extraction)

  • Familiarity with Kubernetes or container orchestration in production

  • Built or contributed to agent frameworks, SDKs, or CLIs

  • Have worked in a startup or fast-paced environments with ownership and ambiguity

  • Passion for developer experience and enabling AI adoption

Benefits

  • Flexible working hours

  • Daily lunch and dinner provided; unlimited snacks and beverages

  • Supportive and highly collaborative work environment

  • Health check-up support and top-tier equipment/hardware support

  • A front-row seat to the generative AI infrastructure revolution

  • Competitive compensation, startup equity, health insurance, and other benefits.

About FriendliAI

FriendliAI is building the world’s best AI inference platform that makes large language and multi-modal models fast, efficient, and deployable at scale. We power high-throughput, low-latency AI workloads for organizations worldwide and integrate directly with Hugging Face, giving developers instant access to over 600,000 open-source models.

We are a small, fast-moving team doing work that matters at one of the most exciting moments in the history of technology. With our world-class inference engine, we are building a platform that the AI industry can actually rely on.

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