AI Engineer

Cygnify; Malaysia; On-site; MYR 180,000 - 240,000; Full time

Job summary

Cygnify is seeking an AI Engineer to design, build and ship AI-native systems—from agentic workflows to RAG pipelines and orchestration layers. You will own end-to-end delivery, partnering with leadership to translate business problems into production-ready AI solutions.

You will work with LangChain and LangGraph, design multi-agent coordination, and ensure reliability, observability and security across complex workflows in a fast-moving startup.

Qualifications

• Degree in Computer Science or a related field.
• Hands-on work in agentic AI and backend engineering.
• Proficient Python development skills.
• Proven experience building agentic workflows and RAG pipelines.
• Experience with LLM APIs and prompt design.
• Strong knowledge of SQL, data modelling and REST APIs.
• Cloud deployment and CI/CD experience.
• Experience shipping AI-native systems used by real users.
• Clear communicator with a product mindset in a startup.
• Experience in HRTech or GTM tech products is a plus.

Responsibilities

• Design and build AI-native systems from end-to-end.
• Develop agentic workflows and multi-agent systems.
• Create orchestration layers coordinating agents, tools, and human inputs.
• Manage state and routing across multi-step workflows.
• Ensure reliability with retries, fallbacks and error handling.
• Build and optimise RAG pipelines (chunking, embeddings, retrieval).
• Design data models and pipelines for search and decision making.
• Work with vector databases and structured data stores.
• Integrate AI systems via APIs and webhooks across platforms.
• Set up evaluation, monitoring and observability for models.

Skills

Python

LangChain

LangGraph

LLM APIs

REST APIs

SQL

CI/CD

Cloud deployment

Agentic AI

Communication

Education

Bachelor's degree in CS or related field

Tools

LangChain

LangGraph

Vector databases

APIs & webhooks

Job description

We're looking for an AI Engineer to design, build and ship AI-native systems, from agentic workflows and RAG pipelines to the orchestration layer that ties them together. You'll own the build end to end, working closely with leadership to turn business problems into production-ready AI system.

Key Responsibilities

• Build agentic workflows and multi-agent systems using LangChain, LangGraph or similar frameworks.
• Design the orchestration layer that coordinates agents, tools and human checkpoints.
• Manage state, memory and routing across long-running, multi-step workflows.
• Build for reliability, with retries, fallbacks and clean failure handling.
• Build and optimise RAG pipelines, from chunking and embeddings to retrieval and re-ranking.
• Design the data models and pipelines that power search, retrieval and decision-making.
• Work with vector databases and structured data stores.
• Connect AI systems with multi-platforms through APIs and webhooks.
• Set up evaluation, tracing and monitoring to track accuracy, drift, latency and cost.
• Build with privacy and security in mind, in line with data protection requirements.

Requirements

• Degree in Computer Science or a related field.
• AI, software or backend engineering, with recent hands-on work in agentic AI.
• Strong Python.
• Proven experience building agents, agentic workflows, RAG and orchestration systems, with LangChain and/or LangGraph in production.
• Experience with LLM APIs, including prompt design and tool use.
• Solid grasp of SQL, data modelling and REST APIs.
• Comfortable with cloud deployment and CI/CD.
• Has shipped AI-native systems used by real users, not just prototypes.
• Clear communicator with a product mindset, comfortable in a fast-moving startup.
• Ideally with experience in building HRTech and/or GTM tech products.
• Experience with LLM evaluation and observability tools.