Lead / Staff Engineer, AI Agent Platform

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

Not verified

401(k) match

Not verified

Was this benefit information wrong? Tell us.

Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Lead / Staff Engineer, AI Agent Platform Suzhou We are building the next-generation Agent Brain. This isn't just another "wrapper around LLM APIs with a chat UI." It is a purpose-built Agent architecture designed for complex knowledge work. Our target scenarios focus on high-value domains like IP and R&D: these involve long-chain tasks, heterogeneous data sources, and strict evidence requirements, ultimately demanding verifiable outcomes rather than just conversational outputs. You will be building a reusable Agent infrastructure and a reasoning/orchestration kernel. Your core focus will be solving three major challenges: How the Agent Runs - Execution Engine: The mechanics of the agent loop. This includes multi-step reasoning cycles, middleware pipelines, Planning & SubAgent orchestration, Checkpointing & state recovery, and execution controls (Permissions / Cost / Clarification). How the Model Thinks per Turn - Context Engineering: It's not about stuffing the context window; it's about organizing attention. You will solve core issues such as: input standardization, determining the exact capabilities and states exposed per turn, compressing long histories into an effective working memory, structured degradation under budget constraints, and normalizing tool outputs into traceable evidence. What the Agent Can Use - Capability Foundation: Sandbox environments (Docker / K8s), Memory Store, MCP Hub, Skills Engine, File System & Upload Pipelines, multi-tenant isolation, security, and observability. If you have a long-term passion for transforming raw model capabilities into robust systems capable of reliably executing complex tasks, this role is a perfect match. We are building the next-generation Agent Brain. This isn't just another

Read the full description at jobs.lever.co. FewerJobs shows a source-linked preview and links to the original posting.