Job Description

About zCloak.AI

zCloak.AI helps enterprises transform business operations through production-ready AI workflows.

We build an AI agent work platform that connects enterprise data, tools, and teams with secure, governed AI execution.

The Role

We are looking for a Forward Deployed AI Engineer to design and deploy AI systems for enterprise customers.

You will take projects from an initial business problem to a working production system. This includes understanding customer workflows, designing the technical architecture, building integrations, deploying AI agents, measuring their performance, and resolving issues in production.

The role combines software engineering, AI systems design, enterprise integration, and customer-facing technical delivery. You should be comfortable moving between code, architecture discussions, deployment environments, and conversations with business and engineering teams.

This role is based in Singapore. You will be expected to participate in an on-call rotation and respond to production incidents when necessary.

What You Will Do

Work directly with customers to understand operational problems and translate them into deployable AI workflows.
Design, build, and deploy production-grade AI agents and agentic systems.
Integrate AI workflows with enterprise APIs, databases, document systems, CRMs, messaging platforms, and internal tools.
Build RAG pipelines, tool-use systems, memory layers, approval flows, and human-in-theloop workflows.
Design permission, authentication, logging, and execution-control mechanisms for enterprise deployments.
Evaluate agent behaviour and improve task completion, accuracy, latency, reliability, and cost.
Trace and resolve problems across models, prompts, tools, data pipelines, application code, and infrastructure.
Participate in on-call rotations, investigate production incidents, and implement fixes that prevent recurring failures.
Work with customer engineering and business teams during pilots, production launches, and post-deployment improvement.
Turn repeated deployment patterns into reusable product components, internal tools, and engineering practices.
Document system architecture, operating procedures, technical decisions, and deployment outcomes.

Minimum Qualifications

Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field, or equivalent practical experience.
Strong programming ability in Python. Experience with TypeScript, Go, Java, or another production language is an advantage.
Experience working in Linux-based development or deployment environments.
Hands-on experience with LLM applications, AI agents, tool calling, or workflow orchestration.
Experience integrating external APIs, databases, and enterprise systems.
Hands-on experience building RAG pipelines using embedding models, vector databases, retrieval techniques, and document-processing tools.
Ability to investigate ambiguous technical problems and take ownership from diagnosis through production deployment.
Clear written and verbal communication skills in English and Chinese.
Willingness to participate in an on-call rotation and respond to production incidents.

Preferred Qualifications

Professional experience building or deploying production software, enterprise systems, or AI applications.
Experience owning a technical project from requirements gathering through production launch and ongoing support.
Experience with one or more agent frameworks or SDKs, such as LangGraph, OpenAI Agents SDK, Google ADK, CrewAI, OpenClaw, Hermes, or equivalent systems.
Familiarity with MCP, agent memory, tracing, observability, evaluation, and prompt or model versioning.
Experience designing multi-agent systems or long-running workflow orchestration.
Familiarity with AWS, Google Cloud, Azure, containers, CI/CD, and infrastructure automation.
Understanding of enterprise security concepts, including identity, permissions, secrets management, audit logs, and data governance.
Experience working in a startup, consulting, solutions engineering, or another fast-moving delivery environment.
Confidence working directly with customers, including gathering requirements, explaining trade-offs, and managing technical expectations.

Candidates with relevant professional experience are preferred. Exceptional fresh graduates with strong AI engineering experience gained through internships, research, open-source contributions, or substantial deployed projects are also encouraged to apply.

What Success Looks Like

A successful Forward Deployed AI Engineer can take an unclear customer problem, identify the workflow and system constraints, build a dependable solution, and get it running in production.

You will make practical engineering decisions, communicate risks clearly, respond calmly when production systems fail, and leave each deployment more reusable and easier to operate than the last.

Apply

If you want to deploy AI systems that operate inside real enterprise workflows, we would like to hear from you.

Please send your CV and, where available, your GitHub profile, portfolio, or examples of relevant projects to: [Confidential Information]k

Email subject

Application – [Position] – [Full Name] – [Experience/School] – [Earliest Start Date]

Learn more about zCloak.AI: www.zcloak.ai