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About the role Lead the end-to-end delivery of production-ready enterprise AI solutions powered by Large Language Models (LLM), Retrieval-Augmented Generation (RAG) and agent-based workflows - owning solution architecture, driving hands-on delivery, and serving as the senior technical point of contact for customers. This is a hands-on leadership role: the person both builds and leads. They take solutions from proof-of-concept to stable production, set delivery and engineering standards, mentor the team, and turn each engagement into reusable capability that scales across multiple customers and use cases. Location: Kuala Lumpur / Petaling Jaya (client site) Salary range : Based on demonstrated output Key Responsibilities Solution design & architecture • Translate customer requirements into practical, scalable solution architectures, workflows and delivery plans. • Own the technical design of AI solutions — knowledge bases, RAG pipelines, agent and workflow automation, authentication and system integration. • Select models, frameworks and configurations based on quality, latency, cost, security and business requirements. • Design modular, reusable AI capabilities that can be applied across multiple customers and use cases. Delivery leadership • Lead delivery from proof-of-concept through to production and continuous optimisation, ensuring quality, security and timeliness. • Mentor and review the work of the AI Solutions Engineer(s); set engineering standards and best practices. • Establish AI evaluation, automated testing, logging and monitoring; drive optimisation of prompts, workflows and model choices. • Plan effort, scope and priorities; manage technical risks and dependencies. Customer & stakeholder engagement • Act as the senior technical lead in customer discussions, demonstrations, proof-of-concepts and implementation workshops (in Bahasa Melayu and English). • Translate business goals into solutions and advise customers on scope, feasibility, delivery sequencing and effort estimates. • Communicate effectively across management, business teams and technical teams. Integration, operations & governance • Oversee integration with customer systems — APIs, databases, messaging channels and enterprise platforms (e.g. CRM / billing). • Address accuracy, hallucination, latency, cost and system-stability issues across the solution lifecycle. • Support LLMOps and software-engineering practices: version control, testing, CI/CD, monitoring, logging and security review. • Ensure solutions meet security, data-privacy, access-control, explainability and audit requirements (PDPA and sector regulations). Job Requirements Education • Degree in Computer Science, AI, Software Engineering, Information Technology, Data Science or a related discipline. Experience • Around 2–3 years of hands-on software / AI delivery experience, including production LLM / RAG / agent solutions delivered from proof-of-concept to production. • Demonstrated experience leading delivery or mentoring engineers, ideally in a customer-facing setting. Software engineering • Strong Python and 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 • Strong command of 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 design and build AI agents and automated workflows. • Familiarity with multimodal AI (documents, images, OCR, voice / audio) is an advantage. • Experience with platforms such as GPTBots.ai, Dify, LangChain or LlamaIndex. • Comfortable using Claude Code and AI-powered IDEs to accelerate delivery. Production delivery • Proven ability to take solutions to production and resolve accuracy, hallucination, latency, cost and stability issues. • Familiar with AI evaluation, automated testing, logging and continuous optimisation. Business understanding & communication • Able to translate business requirements into practical AI solutions. • Able to communicate clearly and credibly with management, business teams and technical teams. Language • Bahasa Melayu — mandatory (spoken and written, professional). • English — mandatory (spoken and written, professional). • Chinese — an advantage, not required. Behavioural Competencies • Strong analytical, troubleshooting and problem-solving skills. • Ability to translate business requirements into practical, maintainable technical solutions. • Strong ownership, accountability and attention to delivery quality. • Good communication, presentation, documentation and cross-functional collaboration skills. • Fast learner with a proactive, adaptable, hands-on mindset and a genuine interest in AI. Ideal Candidate Profile A senior engineer who is not only fluent in AI models, but can also architect and integrate systems, solve real production issues, lead a small delivery team, understand business goals, and communicate clearly across technical and non-technical teams. To Apply Please submit your CV together with a portfolio or links to products you have shipped. Application Without evidence of shipped work will not be shortlisted.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.