AI Solutions Engineer

techstreet; Petaling Jaya; On-site; MYR 60,000 - 110,000; Full time

Job summary

techstreet is seeking an energetic AI Solutions Engineer in Malaysia to design, build, deploy and continuously improve production-ready AI solutions using LLMs and RAG pipelines. You will take projects from proof-of-concept to production, integrating with enterprise systems and optimizing for accuracy, latency and cost.

Responsibilities include developing AI-powered applications, applying prompt engineering, building vector knowledge bases, and ensuring robust monitoring.

Qualifications

• Degree in Computer Science, AI, Software Engineering, Information Technology, Data Science or a related discipline.
• Hands-on experience delivering AI / LLM / chatbot / automation projects, ideally from proof-of-concept through to production.
• Strong project portfolio highly valued.

Responsibilities

• Build and enhance AI-powered applications using LLMs, RAG pipelines and agent/workflow automation.
• Apply prompt engineering, structured outputs, tool calling, validation and fallback techniques to improve accuracy, reliability and consistency.
• Design retrieval and grounding strategies using customer documents, databases and APIs as approved knowledge sources; build and maintain vector search and knowledge bases.
• Select suitable models and configurations based on quality, latency, cost and security requirements.
• Integrate AI services with APIs, backend systems, databases and messaging channels.
• Take solutions from proof-of-concept to production, addressing accuracy, hallucination, latency, cost and system stability.
• Set up AI evaluation, automated testing, logging and monitoring; analyse results and continuously optimise prompts, workflows and model choices.
• Produce clear technical documentation, test reports and operational handover materials.
• Support customer-facing activities - demonstrations, proof-of-concepts and workshops - in Bahasa Melayu and English.

Skills

Python

APIs

Databases

Backend development

System integration

Cloud platforms

Docker

Git

CI/CD

Monitoring

Prompt engineering

RAG

Vector search

Knowledge base

AI agents

Workflow automation

Education

Degree in Computer Science, AI, Software Engineering, Information Technology, Data Science

Tools

Docker

Git

CI/CD

Job description

A hands-on delivery role that designs, builds, deploys and continuously improves production-ready AI solutions powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and agent-based workflows. Working under the Senior AI Solutions Engineer, this person takes solutions from proof-of-concept through to stable production — building intelligent assistants, knowledge systems and workflow automation, integrating them with enterprise systems, and optimising them for accuracy, reliability, latency and cost.

Key responsibilities

Build and enhance AI-powered applications using LLMs, RAG pipelines and agent / workflow automation.

Apply prompt engineering, structured outputs, tool calling, validation and fallback techniques to improve accuracy, reliability and consistency.

Design retrieval and grounding strategies using customer documents, databases and APIs as approved knowledge sources; build and maintain vector search and knowledge bases.

Select suitable models and configurations based on quality, latency, cost and security requirements.

Integrate AI services with APIs, backend systems, databases and messaging channels.

Take solutions from proof-of-concept to production, addressing accuracy, hallucination, latency, cost and system stability.

Set up AI evaluation, automated testing, logging and monitoring; analyse results and continuously optimise prompts, workflows and model choices.

Produce clear technical documentation, test reports and operational handover materials.

Support customer-facing activities - demonstrations, proof-of-concepts and workshops - in Bahasa Melayu and English.

About you

Degree in Computer Science, AI, Software Engineering, Information Technology, Data Science or a related discipline.

Open to fresh graduates or candidates with around 1 year of relevant hands-on experience; a strong project portfolio is highly valued.

Hands-on experience delivering AI / LLM / chatbot / automation projects, ideally from proof-of-concept through to production.

Proficient in Python with sound software-engineering fundamentals.

Experienced with APIs, databases, backend development and system integration.

Familiar with cloud platforms, Docker, Git, CI/CD and monitoring.

Familiar with mainstream large language models and model selection.

Skilled in prompt engineering, structured output and tool calling.

Experienced in RAG, vector search and knowledge-base development.

Able to develop AI agents and automated workflows.