Role Description
This is a full-time on-site role for an AI Solution Architect at Krutrim in Bengaluru. The AI Solution Architect will be responsible for solution architecture, consulting, software development, integration, and optimizing business processes within the AI computing stack infrastructure. The role involves collaborating with cross-functional teams to design and implement AI solutions.
Primary Focus: Utilizing Generative AI models and Krutrim Cloud AI solutions—including Large Language Models (LLMs), Stable Diffusion, and high-performance hardware like NVIDIA A100 and H100 GPUs—to design and implement AI-driven applications for diverse use cases.
Responsibilities
- Leverage LLMs, Stable Diffusion models, and other Generative AI technologies to create innovative solutions.
- Utilize high-performance computing resources (NVIDIA A100, H100 GPUs) to optimize model training and deployment.
- Engage with industrial and healthcare clients to understand their needs and identify opportunities for AI integration.
- Translate business requirements into technical solutions using Krutrim Cloud services.
- Deploy AI applications like NVIDIA Metropolis for smart industries and healthcare systems.
- Ensure scalability, reliability, and efficiency of AI models on Krutrim Cloud infrastructure.
- Provide guidance on best practices for AI model selection, training, and deployment.
- Stay updated with the latest advancements in Generative AI and Krutrim Cloud offerings.
- Ensure all AI solutions comply with industry regulations and ethical standards, particularly in healthcare.
- Conduct workshops and training sessions for clients and internal teams on Generative AI applications.
- Document architectures, processes, and guidelines for future reference.
Must-Have Skills
- Minimum of 10 years of experience in AI solution architecture, machine learning, or related fields.
- Deep understanding of LLMs, Stable Diffusion, and other Generative AI models.
- Experience in training and fine-tuning models for specific use cases.
- Hands-on experience with NVIDIA A100 and H100 GPUs, optimizing AI workloads for high-performance computing environments.
- Strong knowledge of deploying and managing AI solutions on Cloud platforms.
- Familiarity with Applied AI applications in industrial automation, healthcare or financial sectors.
- Proficiency in Python and AI frameworks like TensorFlow and PyTorch.
- Experience with CUDA and GPU programming for performance optimization.
- Proven ability to architect AI solutions from concept to deployment, ensuring they meet business objectives.
- Understanding of industry standards affecting AI deployments.
- Excellent ability to explain complex AI concepts to both technical and non-technical stakeholders.
- Solution Architecture and Consulting skills.
Good-to-Have Skills
- Knowledge of implementing AI solutions for video analytics (e.g., object detection, video summarization) and text analytics (e.g., sentiment analysis, text generation).
- Experience with data pipelines, ETL processes, and handling large datasets.
- Experience deploying AI models on edge devices and understanding of IoT ecosystems.
- Knowledge of CI/CD pipelines, containerization (Docker, Kubernetes), and Infrastructure as Code (IaC) tools.
- Strong background in statistics, data analysis, and ability to interpret model performance and evaluation metrics.