GenAI Engineer

该职位来源于猎聘 Location: Wuxi Job Summary We are looking for a creative and technically proficient GenAI Engineer to design, develop, and implement generative AI solutions that address critical business challenges for Softwareone and our clients. You will work closely with cross-functional teams including data scientists, software engineers, product managers, and client stakeholders to build scalable, secure, and high-performance GenAI applications—ranging from large language model (LLM) fine-tuning to AI-powered workflow automation. This role requires a strong foundation in machine learning, hands-on experience with GenAI frameworks and tools, and a passion for translating cutting-edge AI capabilities into practical business outcomes. Key Responsibilities

• Design, develop, and deploy generative AI models and applications (e.g., LLM-powered chatbots, content generation tools, code assistants, data summarization solutions) tailored to enterprise use cases.
• Fine-tune and optimize open-source (e.g., Llama, Mistral, Falcon) and proprietary (e.g., GPT-4, Claude, Gemini) generative AI models to meet performance, accuracy, and cost requirements.
• Collaborate with data engineers to build and maintain data pipelines for training, validation, and inference of GenAI models, ensuring data quality, privacy, and compliance (e.g., GDPR, CCPA).
• Integrate GenAI solutions with existing enterprise systems, APIs, and cloud platforms (AWS, Azure, Google Cloud) to enable seamless workflow integration and scalability.
• Conduct technical research on emerging GenAI technologies, frameworks, and best practices, and evaluate their applicability to client projects and internal initiatives.
• Debug and troubleshoot GenAI models and applications, addressing issues related to performance, bias, hallucinations, and usability.
• Document technical designs, development processes, model architectures, and deployment procedures to ensure knowledge sharing and compliance.
• Work closely with client stakeholders to understand business requirements, translate them into technical specifications, and deliver GenAI solutions that drive measurable value.
• Mentor junior engineers and contribute to the growth of Softwareone’s GenAI capability and best practices. Required Qualifications & Skills
• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related technical field .
• 4+ years of hands-on experience in machine learning, with a focus on generative AI (LLMs, diffusion models, or transformer-based architectures).
• Proficiency in programming languages: Python (expert level), with experience in ML libraries and frameworks (TensorFlow, PyTorch, Hugging Face Transformers, LangChain, LlamaIndex).
• Hands-on experience fine-tuning and deploying LLMs (e.g., GPT-4, Llama 2, Mistral) using tools like LoRA, QLoRA, or full fine-tuning techniques.
• Familiarity with cloud-based AI services (AWS Bedrock, Azure OpenAI Service, Google Vertex AI) and containerization tools (Docker, Kubernetes) for scalable deployment.
• Strong understanding of NLP concepts (tokenization, embeddings, attention mechanisms) and experience with NLP pipelines (text preprocessing, sentiment analysis, named entity recognition).
• Experience building and maintaining data pipelines for ML, with knowledge of SQL, NoSQL databases, and data processing tools (Spark, Pandas, NumPy).
• Knowledge of software engineering best practices: version control (Git), CI/CD pipelines, unit testing, and agile development methodologies.
• Awareness of AI ethics, bias mitigation, and responsible AI practices, including compliance with data privacy regulations.
• Excellent problem-solving skills, attention to detail, and the ability to work independently and in cross-functional teams.
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders (clients and internal teams). Preferred Qualifications
• Experience developing GenAI solutions for enterprise clients in industries such as finance, healthcare, manufacturing, or retail.
• Knowledge of MLOps tools and practices (MLflow, Weights & Biases, Kubeflow) for model lifecycle management.
• Familiarity with low-code/no-code AI platforms and their integration with custom GenAI solutions.
• Publications or contributions to GenAI/ML communities (e.g., GitHub, Kaggle, conference papers) are a plus.
• Experience with multilingual GenAI models or domain-specific fine-tuning (e.g., legal, technical documentation).
• Be familiar with below technologies:  Database (SQL Server, vector DB)  Python/Django  GenAI Prompt  RAG (AI search experience is preferred)  Multi-agent (AutoGen is preferred)  Docker/AKS, ASE is preferred.  MS Azure Cloud  MS Azure DevOps
• Fluent English skill on both spoken and writing.
• Strong organizational, and project management skills
• Excellent communication and interpersonal skills
• Knowledge of technical architecture, software development, computer system verification and cybersecurity
• Document generation and review experience
• Ability to work under pressure and meet tight deadlines
• Strong problem-solving and analytical skills