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Stripe is looking to solve the problem of how users interact with their financial infrastructure platform by building an intelligent and proactive assistant that not only answers user queries but efficiently resolves issues and provides valuable business insights. This assistant aims to elevate the user experience across Stripe, from the dashboard to support surfaces, and enable other teams to build and integrate their AI agents on the platform, ultimately increasing the GDP of the internet.

Requirements

• Strong backend or full‑stack engineering background with solid distributed systems fundamentals (e.g., concurrency, consistency, caching, data modeling, fault tolerance).
• Proficient in at least one modern programming language (e.g., Ruby, Python, TypeScript) and comfortable working across the stack when needed.
• Experience designing, implementing, and maintaining APIs and services with high reliability requirements.
• Practical experience integrating or consuming LLM-based services (e.g., RAG, embeddings, function calling, or agent frameworks) in user-facing products or internal tools.
• Experience working closely with ML engineers, product managers, and designers to translate product requirements into robust technical solutions.
• Experience shipping applied LLM or AI-powered features at scale to end users, with attention to safety, reliability, and user experience.
• Experience building or evolving platforms that multiple teams use (e.g., shared APIs, internal developer platforms, or extensibility frameworks).

Responsibilities

• Design and operate backend services and APIs that power the Assistant’s core workflows—conversation routing, tool and agent orchestration, state management, and grounding in Stripe data.
• Integrate LLM and agentic capabilities (e.g., RAG, tool use/function calling, summarization) into production systems in a scalable, observable, and cost‑efficient way.
• Establish trustworthy, human-in-the-loop execution for high-trust “write” actions and define the permissions, safety checks, and governance model for tools and agents.
• Build the infrastructure for conversation continuity, personalization, and cross-surface memory so the Assistant can act as a persistent, context-aware partner in the dashboard and beyond.
• Develop evaluation, experimentation, and telemetry pipelines to measure answer quality, reliability, and latency—and use them to drive iterative product and system improvements.
• Elevate operational excellence and technical quality: define and meet SLOs, improve security and observability, mentor other engineers, and help shape architectural direction.
• Collaborate closely with ML engineers, product managers, designers, and other teams across Stripe to plan roadmaps, make pragmatic tradeoffs, and ship impactful features quickly and safely.

Other

• 6+ years of professional software engineering experience building and operating production services.
• Experience working in highly ambiguous problem spaces, setting technical direction, and driving alignment across teams.