Strategic AI Solutions Architect

2 days ago

Mount Abu, Rajasthan, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,25,00,000
AI Solutions Developer

Develop innovative AI solutions that drive business value by leveraging Large Language Models (LLMs), cloud-agnostic platforms, and cutting-edge SaaS development trends.

  • Design, develop, and deploy scalable SaaS products using advanced LLMs like Meta, Azure OpenAI, Claude, and Mistral.
  • Ensure secure, efficient, and high-performance architecture for SaaS products.
  • Collaborate closely with product management and stakeholders to align AI-driven SaaS solutions with business strategies and customer expectations.
  • Fine-tune AI models using custom instructions to tailor them to specific use cases and optimize performance through techniques like quantization and model tuning.
  • Architect AI deployment strategies using cloud-agnostic platforms (AWS, Azure, Google Cloud), ensuring cost optimization while maintaining performance and scalability.
  • Apply retrieval-augmented generation (RAG) techniques to build AI models that provide contextually accurate and relevant outputs.
  • Build the integration of APIs and third-party services into the SaaS ecosystem, ensuring robust and flexible product architecture.
Qualifications
  • Bachelor's degree or equivalent in Information Systems, Computer Science, or related fields.
  • 6+ years of experience in product development, with at least 2 years focused on AI-based SaaS products.
  • Demonstrated experience in leading the development of SaaS products, from ideation to deployment, with a focus on AI-driven features.
  • Hands-on experience with LLMs (Meta, Azure OpenAI, Claude, Mistral) and SaaS platforms.
  • Proven ability to build secure, scalable, and compliant SaaS solutions, integrating AI with cloud-based services (AWS, Azure, Google Cloud).
  • Strong experience with RAG model techniques and fine-tuning AI models for business-specific needs.
  • Proficiency in AI engineering, including machine learning algorithms, deep learning architectures (e.g., CNNs, RNNs, Transformers), and integrating models into SaaS environments.
  • Solid understanding of SaaS product lifecycle management, including customer-focused design, product-market fit, and post-launch optimization.
  • Excellent communication and collaboration skills, with the ability to work cross-functionally and drive SaaS product success.

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