AI Agent Platform Engineer (Openclaw)

Binance is a leading global blockchain ecosystem behind the world's largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products.

Binance is building one of the largest internal AI agent fleets in the industry — hundreds of sandboxed agents powering automation across trading, compliance, customer service, risk, and beyond. This role sits at the core of that platform: you'll build the infrastructure and tooling that makes every agent faster, smarter, and more impactful — directly translating into operational efficiency gains and accelerating business growth.

We're looking for a strong individual contributor who stays close to the frontier and has the instinct to turn promising ideas into working implementations. This is a builder role. You'll own the full stack from agent skill authorship to infrastructure tuning, and you'll be the person who spots a new technique in the wild and figures out how to make it real inside our platform.

Responsibilities:

• Build, publish, and maintain OpenClaw skills — modular capability units used by hundreds of agents across the org
• Develop CLI tooling for agent operations: deployment, diagnostics, session management, skill registry, developer workflows
• Own end-to-end AI agent harness engineering: lifecycle management, tool execution, context/session tuning, compaction strategies, model routing
• Instrument the agent fleet with data pipelines and dashboards; apply data science techniques to understand token efficiency, failure modes, latency distribution, and business outcome correlation
• Identify bottlenecks across the platform and drive measurable improvements in agent throughput, response quality, and cost efficiency
• Track the research frontier — papers, open-source releases, community developments — and rapidly prototype integrations
• Optimize LLM infrastructure: token budgeting, multi-provider routing, cost attribution, context window management
• Harden agent sandboxes: credential isolation, prompt injection defense, guardrails
• Partner with product and business teams to translate user growth goals into reliable, scalable agent workflows

Requirements:

• 5+ years in software/platform engineering; 2+ year hands-on with LLM or AI agent systems in production
• AI Native mindset — you default to AI-assisted development, think natively in agent/tool/context primitives
• Skill & CLI development: experience building modular, composable tools or CLI utilities for developer platforms; TypeScript and/or Python fluency
• Agent harness engineering: practical experience with OpenClaw, LangGraph, AutoGen, CrewAI, or equivalent orchestration runtimes
• LLM infrastructure: token management, model routing, context compaction, cost optimization at scale
• Data science capability: comfortable with log analysis, statistical profiling, SQL/Python for usage data
• Research awareness: follows model releases, agent framework updates, and relevant literature

Nice to have:

• Direct experience with OpenClaw — session config, hooks, cron/heartbeat architecture, skill registry (ClawHub)
• Familiarity with CLI and the agent tooling ecosystem
• LiteLLM / AWS Bedrock / multi-provider proxy experience
• Kubernetes/EKS: pod isolation, resource tuning, secrets management
• Security engineering background: sandbox escapes, prompt injection, guardrail design

Location: Asia (Singapore); Hong Kong. Hybrid workplace.