Agentic Engineer II - AI Agents (Customer Agents)
At a glance
Mid-level AI Engineering role at WATI.io. Shenzhen.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build customer-facing agents with conversation flows, knowledge retrieval, tool use, human handoff and messaging integrations
- Develop LLM services with prompts, context handling, retrieval, safeguards, fallbacks and structured tool execution
- Track answer quality, task completion, latency, cost and failure patterns through evaluation and observability workflows
- Turn customer problems into shipped agent experiences with product, design and customer-facing teams
- Improve shared platform tools for APIs, testing, deployment, monitoring and developer workflows
What you bring
- Four to seven years in software engineering, with solid backend or full-stack experience
- You have shipped production software using Python, TypeScript or a comparable language
- Hands-on experience building LLM applications, such as retrieval systems, agents, tool use or evaluation workflows
- You can debug and own work across product and infrastructure, weighing reliability, privacy, speed and cost
Who this fits
This is a hands-on senior individual-contributor role for an engineer who likes delivering end-to-end product capabilities and improving the underlying platform. The position is onsite in Shenzhen, China.
From the employer
About Wati
Started as a WhatsApp team inbox in 2020, Wati has evolved into an AI-powered customer engagement platform that goes beyond a single channel. Designed for businesses that sell, support, and grow through conversations, Wati observes customer intent in real time, decides the next best revenue action, and executes it across marketing, sales, and support — on WhatsApp, Instagram, Facebook, TikTok, SMS, and more.
Trusted by over 16,000 customers across 190+ countries, Wati simplifies complex operations and business conversations with a unified inbox, no-code automation, and our intelligent AI layer, Astra.
Proudly backed by Tiger Global, Sequoia Capital, DST Global, and Shopify, and recognised as a Premium Partner of Meta and Google.
Wati, the AI-Powered Customer Engagement Platform for Revenue Growth.
About the Role
We are hiring a hands-on Senior Software Engineer to build customer-facing AI agents and the shared platform capabilities that make them work at scale. You will work closely with product, design, and platform engineers to turn LLM capabilities into reliable, measurable customer experiences.
This is a senior individual-contributor role for a builder: someone who enjoys shipping end-to-end product capabilities, making pragmatic technical decisions, and improving the foundations as the product grows.
What You Will Do
- Build and operate customer-agent capabilities, including conversation flows, knowledge retrieval, tool calling, human handoff, and messaging-channel integrations.
- Develop reliable LLM application services: prompts, context management, RAG, guardrails, fallback behavior, and structured tool execution.
- Build evaluation and observability workflows that measure answer quality, task success, latency, cost, and common failure modes.
- Partner with product, design, and customer-facing teams to turn real customer problems into shipped agent experiences.
- Improve the shared agent platform where needed: reusable primitives, APIs, testing, deployment, monitoring, and developer experience.
- Contribute to technical design and raise engineering quality through thoughtful implementation and code reviews.
Requirements
What We Are Looking For
- 4-7 years of software-engineering experience, with strong backend or full-stack foundations.
- Experience shipping production systems with Python, TypeScript, or similar languages.
- Practical experience building LLM-powered applications, such as RAG, tool calling, agents, evaluation systems, or AI workflow automation.
- Strong ownership and debugging skills, and comfort working across product and infrastructure boundaries.
- Sound engineering judgment around reliability, privacy, latency, and cost in customer-facing systems.
- Clear written and spoken communication in a fast-moving, collaborative team.
Nice to Have
- Experience with multi-tenant SaaS, conversational products, messaging platforms, or customer-support automation.
- Experience with LLM gateways, model providers, observability, experimentation platforms, or AI evaluation.
- Experience with voice or realtime AI.