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Generative AI Solutions Architect
2 months ago
We are looking for a talented Generative AI Solutions Architect to spearhead the architecture, development, and collaborative creation of innovative generative AI applications.
Position SummaryThe successful candidate will possess both practical and architectural expertise, adept at assessing and steering various AI initiatives while partnering closely with client teams.
Key Responsibilities- Design and construct scalable, enterprise-level AI solutions utilizing LLMs and other machine learning models, particularly addressing challenges in the healthcare sector.
- Ensure that AI systems uphold principles of privacy, security, and fairness, while complying with responsible AI standards.
- Architect and deploy AI outputs in diverse formats (such as JSON, arrays, HTML) to facilitate smooth integration into dashboards.
- Develop flexible API integrations and low-code UI/UX solutions with rapid development cycles.
- Optimize AI workflows, including data preprocessing, feature extraction, model training, and evaluation.
- Utilize frameworks (like TensorFlow and PyTorch) and open-source platforms such as Hugging Face.
- Collaborate with Product Development as a subject matter expert in Generative AI.
- Create comprehensive documentation and convey complex AI concepts to a variety of stakeholders.
- Establish best practices and standards for generative AI development within the organization.
- Bachelor's degree in Computer Science, AI, or a related discipline.
- Over 5 years of full-stack engineering experience with programming languages such as C# and Python, alongside proficiency in architectural design.
- Proven experience in deploying enterprise AI systems in production environments, including computer vision and natural language processing.
- Strong grasp of natural language generation, generative AI, transformers, LLMs, and text embeddings.
- Minimum of 3 years in a technical leadership capacity, guiding project teams and establishing technical direction.
- Expertise in machine learning libraries and frameworks (including PyTorch, TensorFlow, Hugging Face, LangChain, Llama Index).
- Experience with cloud services (AWS, GCP, or Azure) and containerization technologies.
- Exceptional problem-solving abilities and a capacity for critical and creative thinking.
- Experience with self-supervised learning, transfer learning, and reinforcement learning.
- Familiarity with vector databases such as Pinecone.
- Understanding of AI ethics and responsible AI practices.
