AI Solutions Engineer (Petaling Jaya)

techstreet; Selangor; On-site; MYR 72,000 - 120,000; Full time

Job summary

techstreet in Malaysia is seeking an hands-on AI Solutions Engineer to design, build, deploy and improve production-ready AI solutions using LLMs, RAG and agent-based workflows. You'll take concepts from proof-of-concept to production, integrating with enterprise systems and optimizing for accuracy, latency and cost.

The role requires strong Python and software engineering fundamentals, experience with APIs, databases, cloud platforms, Docker, Git, CI/CD and monitoring, plus hands-on AI

Qualifications

• Degree in CS/AI/Software Engineering/IT/Data Science or related field.
• 1 year of relevant hands-on AI/LLM experience; strong project portfolio preferred.
• Hands-on AI/LLM, chatbot and automation project delivery from PoC to production.
• Proficient in Python with solid software engineering fundamentals.
• Experience with APIs, databases, backend development and system integration.
• Familiar with cloud platforms, Docker, Git, CI/CD and monitoring.
• Knowledge of LLMs, prompt engineering, tool calling and RAG.

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.
• Design retrieval/grounding strategies; build vector search and knowledge bases.
• Select models/configurations based on quality, latency, cost and security.
• Integrate AI services with APIs, databases and enterprise systems.
• Take solutions from PoC to production; address accuracy, latency, and stability.
• Set up AI evaluation, testing, logging and monitoring; optimise prompts/workflows.
• Produce clear technical documentation and handover materials.
• Support customer-facing activity in Bahasa Melayu and English.

Skills

Python

APIs

Databases

Backend

System Integration

Cloud Platforms

Docker

Git

CI/CD

Monitoring

LLMs

Prompt Engineering

Tool Calling

RAG

Vector Search

Knowledge Base

AI Agents

LangChain

LlamaIndex

Claude Code

Education

Bachelor’s degree in Computer Science, AI, Software Engineering, IT, Data Science

Tools

Docker

LangChain

LlamaIndex

Claude Code

Job description

Jora Malaysia will close on 9th September 2026. Thank you for being with us, we are cheering you on as you continue your career journey.

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.

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.

Requirements

• Education:
• Degree in Computer Science, AI, Software Engineering, Information Technology, Data Science or a related discipline.
• Experience:
• 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.
• Software engineering:
• 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.
• Hands-on AI expertise:
• 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.
• Familiarity with multimodal AI (documents, images, OCR, voice / audio) is an advantage.
• Exposure to platforms such as GPTBots.ai, Dify, LangChain or LlamaIndex is an advantage.
• Comfortable using Claude Code and AI-powered IDEs to accelerate delivery.
• Able to address accuracy, hallucination, latency, cost and system-stability issues.
• Familiar with AI evaluation, automated testing, logging and continuous optimisation.
• Able to translate business requirements into practical AI solutions.
• Able to communicate effectively with management, business teams and technical teams.
• Language:
• Bahasa Melayu — mandatory (spoken and written, professional).
• English — mandatory (spoken and written, professional).
• Mandarin — an advantage, not required.
• Strong analytical, troubleshooting and problem-solving skills.
• Strong ownership and attention to delivery quality.
• Fast learner with a proactive, hands-on mindset and a genuine interest in AI.
• Clear communicator across both technical and non-technical audiences.
• Ideal Candidate Profile:
• An engineer who is not only familiar with AI models, but can also integrate systems, solve real production issues, understand business goals, and communicate clearly across technical and non-technical teams.