
Senior AI Software Engineer
2 days ago
Job Overview:
We are seeking an agile AI software developer with a strong focus on both AI engineering and SaaS product development in a 0-1 product environment. This role is perfect for a candidate skilled in building and iterating quickly, embracing a fail-fast approach to bring innovative AI solutions to market rapidly.
Responsibilities:
- Design, develop, and deploy SaaS products leveraging Large Language Models (LLMs), including platforms like Meta, Azure OpenAI, Claude, and Mistral.
- Support the product lifecycle from conceptualization to deployment, ensuring seamless integration of AI models with business requirements and user needs.
- Build secure, scalable, and efficient SaaS products that embody robust data management and comply with security and governance standards.
- Collaborate closely with product management, and other 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.
- Integrate APIs and third-party services into the SaaS ecosystem, ensuring robust and flexible product architecture.
- Monitor product performance post-launch, iterating and improving models and infrastructure to enhance user experience and scalability.
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.
- Knowledge of cost-optimized AI deployment and cloud infrastructure, focusing on scalability and performance.
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