AI Platform Engineer (Generative & Agentic AI)

Key Responsibilities: 

• Develop Generative AI/Agentic AI software solutions and platforms, ensuring alignment with Lenovo's strategic goals and enterprise technical standards.
• Build AI solutions, including architectures, inference engines, agents, and user interfaces.
• Develop end-to-end AI systems using large language models (LLMs), small language models (SLMs), vision language models (VLMs), and leverage technologies such as MCP and open-source frameworks.
• Integrate AI solutions into existing platforms/systems, including on-premise and edge implementations.
• Identify and implement AI tools, frameworks, and technologies that enhance the effectiveness and efficiency of AI solutions.
• Incorporate robust security measures into AI solutions, including data encryption, access controls, and vulnerability assessments.
• Implement best practices for AIOps and AI development for both experimental and production environments.
• Adhere to coding guidelines and best practices across projects, ensuring high-quality and maintainable AI software development.
• Produce detailed documentation, including system diagrams, data flows, integration points, and technical specifications.
• Stay current with advancements in AI technologies and propose innovative implementation strategies.
• Participate in pre-sales discussions, solution design sessions, and RFP/RFI responses to support enterprise AI opportunities.
• Communicate technical concepts and solution approaches clearly to both technical and non-technical stakeholders.

Qualifications: 

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
• 5+ years in AI development and implementation roles across domains such as data science, machine learning, NLP, computer vision, or Generative AI.
• 2+ years of experience in developing Generative AI end-to-end solutions, including multi-modal solutions utilizing NVIDIA, cloud-based LLMs, or open-source models (e.g., OpenAI, Anthropic, Llama, Hugging Face, Bedrock).
• Experience with NVIDIA technologies (e.g., GPUs, CUDA, TensorRT) and integrating tools from NVIDIA AI Enterprise in on-premise solutions is a plus.
• Strong knowledge of on-premise and cloud environments, particularly with containerization and scaling using Kubernetes.
• Proven experience in implementing MLOps, LLMOps, or AIOps, and managing CI/CD pipelines for AI deployment using tools such as Jenkins, GitLab, or similar.
• Strong programming skills in languages such as Python, React, and scripting languages.

If you are passionate about AI development and eager to take on a challenging yet rewarding role that makes a real impact, we invite you to connect with us!