
Cloud-Native AI Solutions Architect
1 week ago
We are seeking a visionary leader to spearhead our next-generation AI initiatives. This role demands expertise in Large Language Models (LLMs) integration, cloud-native architecture, and hands-on leadership in delivering scalable GenAI solutions on cloud platforms.
Key Responsibilities:
- Design, develop, and deploy GenAI projects leveraging LLMs on cloud platforms, primarily AWS.
- Architect and implement scalable, event-driven cloud-native solutions using AWS Lambda, SNS/SQS, Step Functions, and related services.
- Drive prompt engineering strategies including prompt versioning, optimization, and chain-of-thought design to enhance model performance.
- Oversee fine-tuning, embeddings, and conversational flow development to build intelligent, context-aware AI applications.
- Integrate and manage LLM APIs such as Azure OpenAI and other emerging models to deliver cutting-edge AI capabilities.
- Utilize vector databases for embedding-based search and Retrieval-Augmented Generation (RAG).
- Lead model evaluation efforts including output analysis, performance tuning, and quality benchmarking to ensure high standards.
- Collaborate with cross-functional teams to align AI solutions with business goals.
- Mentor technical teams on best practices in GenAI development and cloud architecture.
- Stay abreast of the latest advancements in AI, cloud technologies, and LLM frameworks to continuously innovate and improve solutions.
Requirements:
- Strong leadership skills with experience in managing cross-functional teams.
- Expertise in Large Language Models (LLMs) integration and cloud-native architecture.
- Hands-on experience in designing, developing, and deploying GenAI projects on cloud platforms.
- Proficiency in AWS Lambda, SNS/SQS, Step Functions, and related services.
- Ability to drive prompt engineering strategies and optimize model performance.
- Experience in fine-tuning, embeddings, and conversational flow development.
- Knowledge of vector databases and Retrieval-Augmented Generation (RAG).
- Ability to collaborate with cross-functional teams and mentor technical teams.
Benefits:
- Opportunity to work on cutting-edge AI initiatives.
- Collaborative and dynamic work environment.
- Professional growth and development opportunities.
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