About the Role
We are seeking an Senior AI Engineer who combines deep technical mastery with curiosity and creativity in leveraging AI tools to design, build, and refine next-generation solutions.
This role is ideal for someone with deep hands-on experience in generative AI, large language models (LLMs), and Retrieval-Augmented Generation (RAG), who thrives in fast-paced environments and is passionate about solving real-world problems through AI.
Responsibilities
- Leverage AI tools and frameworks not only for automation but as creative partnersexperimenting with prompts, refining outputs, and integrating generative models into the development workflow.
- Demonstrate critical evaluation of AI-generated results, ensuring quality, maintainability, and reliability.
- Lead the design, development, and deployment of generative AI systems, including LLM-based agents and RAG pipelines.
- Collaborate with cross-functional teams (PMs, data scientists, backend engineers) to define product scenarios and optimize AI workflows.
- Architect scalable AI solutions using modern cloud platforms (Azure) and MLOps tools (MLFlow, Kubeflow, CI/CD).
- Implement and optimize vector databases (e.g., FAISS, Pinecone, Qdrant) and retrieval systems for enterprise knowledge integration.
- Drive prompt engineering, model fine-tuning, and performance evaluation strategies.
- Contribute to the team's technical roadmap, mentor junior engineers, and promote best practices in AI development.
Qualifications
- Master's degree or higher in an AI-related field.
- Proven experience with generative AI, LLMs (OpenAI), and RAG architectures.
- Strong programming skills in Python and familiarity with frameworks like LangChain, LangGraph, FastAPI.
- Experience with cloud-native AI development (Azure AI Studio, Cognitive Search, AKS, Azure ML).
- Solid understanding of backend systems, microservices, and distributed computing.
- Familiarity with MLOps practices and tools for scalable deployment and monitoring.
- Excellent communication skills and a proactive mindset to contribute ideas beyond assigned tasks.
Preferred
- Preferred Experience in building production-grade AI agents for enterprise use cases. Background in NLP, transformers, and model orchestration.
- Prior contributions to open-source AI projects or publications.
Project Background
The Speech Project was launched in 2003, establishing a strong and trustworthy partnership with the client. The project primarily focuses on cloud-based platforms and big data computing, involving: the training and iterative optimization of acoustic and language models for speech recognition, the development of automated tools and systems related to speech recognition model building, and experimental research on cutting-edge technologies in speech recognition.
Project Highlights
Leverage top-tier AI service platforms to gain exposure to cutting-edge AI technologies and application ecosystems worldwide
Collaborate with global teams and engineers from multiple countries, enhancing international perspective and cross-cultural communication skills
Outstanding performers will have access to fast-track career development opportunities.
