Procurement Agent Engineer

职位描述

About the team:

We are transforming the traditional procurement system into an AI-native procurement platform, with a strong focus on building Procurement Agents. As part of ByteDance’s Corporate Information department, we design and operate corporate service systems that power the company’s global growth and enhance the daily efficiency and experience of employees worldwide.

Procurement is a complex, high-value domain defined by long workflows, rich business rules, and real decision-making — and one of the most promising arenas for applying cutting-edge AI Agent technology to large-scale, real-world problems. We are reimagining how employees and business partners interact with procurement through intelligent agents, and building the underlying System AI Harness that lets agents plan, act, and deliver reliably.

You will work at the frontier of AI Agent engineering while developing deep, end-to-end mastery of a complex business domain — exploring emerging technologies and driving lasting impact across both our products and technical foundations.

Responsibilities:

- Own Procurement Agents and the underlying System AI Harness end to end — from architecture and design through implementation, validation, release, and continuous iteration — leading medium-to-large initiatives to production.

- Design, build, and evolve the core backend services, business logic, data flows, and integrations behind AI-native procurement, with a focus on maintainability, scalability, performance, and operational stability.

- Lead the design and productionization of AI Agent capabilities (planning, tool use, memory, multi-step reasoning, orchestration), turning emerging LLM techniques into reliable, production-grade features that solve real procurement problems at scale.

- Prototype rapidly and evaluate emerging AI techniques with rigor, turning proven approaches into durable platform capabilities and engineering standards.

- Partner with product, design, and cross-functional teams to break down ambiguous, complex problems and ship complete end-to-end solutions.

- Drive continuous improvements in reliability, performance, and code quality through systematic analysis, tuning, and engineering excellence initiatives.

- Mentor teammates through reviews, architecture guidance, and knowledge sharing.

- Drive mid‑to‑long‑term technical roadmaps with clear evolution strategies.

- Solve complex problems with proven approaches, and help the team tackle challenges more effectively.

任职要求

Minimum Qualifications:

- Bachelor’s degree or above in Computer Science, Software Engineering, or a related field.

- 4+ years of backend development experience (or equivalent depth), with a proven track record of owning complex, medium-to-large systems end to end.

- Proficient in Golang / Java / Python (one or more), with solid backend architecture experience and the ability to lead the design of complex services and modules.

- Solid distributed-systems foundation — messaging middleware, relational databases, caching, async processing, and common patterns (idempotency, retries, rate limiting, eventual consistency) — with hands-on experience building stable, extensible distributed services.

- Hands-on AI project experience (LLM applications, Agents, RAG, tool/function calling, or AI-powered features), with the ability to take AI capabilities from prototype to reliable production.

- Strong performance analysis and tuning skills, solid reliability engineering and observability practices, and experience operating production systems at scale.

- Strong logical thinking and problem-breakdown ability, with experience driving ambiguous problems to concrete, shippable solutions.

Preferred Qualifications:

- Experience building platformized products or shared services across multiple domains, with strong abstraction, domain modeling, and extensibility design skills.

- Deep experience designing and operating large-scale, high-concurrency distributed services, with a focus on high availability, scalability, fault tolerance, and graceful degradation.

- Hands-on experience with AI-powered applications, Agent-based products, or AI coding / developer-productivity tools; familiarity with prompt engineering, RAG, function/tool calling, agent orchestration, and evaluation.

- Practical AI application experience in procurement, supply chain, or other enterprise domains (recommendation, forecasting, optimization, intelligent automation).

- Demonstrated technical leadership in driving cross-team alignment, setting technical direction, and delivering results in complex environments, including mentoring junior engineers.

- Strong drive to turn emerging AI technologies into high-impact products; high-quality open-source contributions, research publications, or top-tier competition achievements are a plus.