Forward Deployed AI Engineer

ZERO BYTE LABS PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

ZERO BYTE LABS PTE. LTD. seeks aForward Deployed AI Engineer to design and deploy enterprise AI solutions for customers.

You will translate client workflows into practical technical implementations, taking projects from discovery to deployment in a hands-on, customer-facing capacity. The role requires strong Python skills, experience with LLM apps and integrations, and the ability to work across APIs, databases, and internal tools.

Qualifications

• Proficiency in Python and strong software engineering fundamentals.
• Hands-on experience with LLM apps, AI agents, tool usage, or RAG.
• APIs, databases, software integrations, testing, and debugging.
• Familiarity with Linux-based development or deployment environments.
• Strong problem-solving skills and ability to translate business requirements into practical technical solutions.
• Strong written and verbal communication in English; Mandarin Chinese proficiency required for collaboration.

Responsibilities

• Understand customer workflows and translate problems into deployable AI workflows.
• Design, build, and deploy production-ready AI agents and agentic workflows.
• Integrate AI solutions with enterprise APIs, databases, document systems, and internal tools.
• Build RAG, tool-use, memory, approval, and human-in-the-loop workflows.
• Support pilots, implementation, testing, deployment, and post-deployment improvements.
• Evaluate and improve task success, accuracy, reliability, latency, and cost.
• Diagnose issues across models, prompts, retrieval, tools, data, integrations, and application logic.
• Respond promptly to urgent customer or production issues and implement fixes.
• Turn repeated customer requirements into reusable product components.

Skills

Python programming

LLM applications

APIs & databases

Linux environments

problem solving

business requirements to solutions

English communication

Mandarin Chinese

Education

Bachelor's degree in CS/Software Eng/AI-ML

Tools

LangGraph

OpenAI Agents SDK

Google ADK

CrewAI

Cloud platforms

Containers

Job description

About Us

We build enterprise AI systems that connect company knowledge, AI agents, tools, and business workflows.

Our product, Counso.AI, helps enterprises turn business processes into secure, governed, and repeatable AI workflows. We work closely with financial institutions, professional services firms, and other enterprises with complex data, security, integration, and workflow requirements.

The Role

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

You will work directly with customers to understand their workflows, translate business requirements into practical technical solutions, and take projects from discovery through implementation and deployment.

This is a hands‑on, customer‑facing engineering role. You should be comfortable moving between coding, system design, integrations, deployment, troubleshooting, and stakeholder communication. The role also requires timely response to urgent customer or production issues when reasonably required.

What You Will Do

• Work with customers to understand operational problems and translate them into deployable AI workflows.
• Design, build, and deploy production‑ready AI agents and agentic workflows.
• Integrate AI solutions with enterprise APIs, databases, document systems, and internal tools.
• Build RAG, tool‑use, memory, approval, and human‑in‑the‑loop workflows.
• Support pilots, implementation, testing, deployment, and post‑deployment improvement.
• Evaluate and improve task success, accuracy, reliability, latency, and cost.
• Diagnose issues across models, prompts, retrieval, tools, data, integrations, and application logic.
• Respond promptly to urgent customer or production issues and implement practical fixes or workarounds.
• Turn repeated customer requirements and deployment patterns into reusable product components.

What We Are Looking For

• Strong Python programming skills and solid software engineering fundamentals.
• Hands‑on experience with LLM applications, AI agents, tool calling, workflow orchestration, or RAG.
• Experience with APIs, databases, software integrations, testing, and debugging.
• Familiarity with Linux‑based development or deployment environments.
• Strong problem‑solving skills and the ability to investigate ambiguous technical issues.
• Ability to understand business requirements and translate them into practical technical solutions.
• Strong written and verbal communication skills in English.
• Proficiency in Mandarin Chinese is required for regular collaboration with Mandarin‑speaking stakeholders.
• Willingness and ability to respond promptly to urgent customer or production issues when reasonably required.
• Bachelor's degree in Computer Science, Software Engineering, AI/ML, or a related technical field, or equivalent practical experience.

Nice to Have

• Experience building or deploying production AI applications or enterprise systems.
• Experience owning technical projects from requirements gathering through deployment.
• Familiarity with agent frameworks such as LangGraph, OpenAI Agents SDK, Google ADK, CrewAI, or similar systems.
• Experience with cloud platforms, containers, CI/CD, tracing, observability, or evaluation.
• Understanding of enterprise security concepts such as identity, permissions, secrets, audit logs, and data governance.
• Experience in consulting, solutions engineering, implementation, professional services, or another customer‑facing technical environment.

Who Should Apply

Candidates with relevant professional experience are preferred. Fresh graduates with strong hands‑on experience through internships, research, open‑source contributions, or substantial deployed projects are also encouraged to apply.

What Success Looks Like

You can take an unclear customer problem, identify the workflow and technical constraints, build a practical solution, and get it implemented successfully.

You can communicate technical trade‑offs clearly, troubleshoot issues systematically, respond promptly when problems arise, and turn deployment experience into reusable product improvements.