Deskripsi Pekerjaan
Are you ready to redefine the software development lifecycle? Luxoft is looking for a visionary AI-Native Engineering Lead to join our Singapore team. In this role, you will be at the forefront of the AI revolution, moving beyond simple integration to architecting agentic AI workflows that fundamentally change how we build, test, and maintain enterprise-grade software.
We are seeking a technical leader who understands that AI isn't just a tool—it's the core of the new engineering paradigm. You will lead the charge in implementing GenAI and Agentic AI frameworks to automate complex coding tasks, enhance documentation, and streamline troubleshooting processes. You will build reusable GenAI components and leverage the Model Context Protocol (MCP) to bridge the gap between AI models and real-world development environments.
If you are passionate about developer productivity, possess a deep understanding of LLMs, and have the architectural vision to scale AI solutions, we want to hear from you.
Tanggung Jawab
- Architect and implement GenAI-driven workflows to automate the full Software Development Life Cycle (SDLC).
- Design and deploy agentic AI systems that perform complex engineering tasks, including code generation, debugging, and system analysis.
- Develop and maintain reusable GenAI assets and internal tools to standardize AI integration across engineering teams.
- Champion the adoption of Model Context Protocol (MCP) to integrate disparate data sources into AI agent environments.
- Collaborate with product and engineering stakeholders to identify high-impact areas for AI automation.
- Mentor engineering squads on AI-native coding practices and prompt engineering excellence.
- Monitor the performance, accuracy, and security of AI-integrated workflows to ensure enterprise reliability.
Kualifikasi
- Bachelor’s or Master’s degree in Computer Science, AI, or a related technical field.
- 5+ years of experience in software engineering with a strong track record of delivering scalable enterprise systems.
- Hands-on experience with LLM frameworks (LangChain, LlamaIndex, AutoGPT) and modern AI agent architecture.
- Deep understanding of the Model Context Protocol (MCP) and integrating AI models into existing IDE/DevOps toolchains.
- Strong proficiency in Python or TypeScript, with experience building high-performance APIs and microservices.
- Demonstrated expertise in prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning LLMs for code synthesis.
- Excellent communication skills with the ability to bridge the gap between highly technical AI concepts and business goals.
- Prior experience in a technical leadership or team lead role is highly preferred.