Key Responsibilities:
- Design, implement, and maintain AI solutions, including generative AI tools and prompt engineering.
- Develop and deploy AI models using AWS Bedrock and other cloud platforms.
- Implement RAG (Retrieval-Augmented Generation) use cases and chatbot solutions.
- Work with vector databases to enhance AI model performance.
- Collaborate with cross-functional teams to understand requirements and deliver innovative AI solutions.
- Develop and maintain CI/CD pipelines for AI models.
- Troubleshoot and resolve advanced issues related to AI infrastructure and deployments.
- Mentor and guide junior team members, fostering a culture of continuous learning and innovation.
- Drive best practices and standards for AI engineering within the organization.
- Manage and prioritize multiple projects and initiatives in a fast-paced environment.
Required Skills and Experience:
- Experience in AI engineering and related fields.
- Strong knowledge of AI concepts and generative AI tools.
- Proficiency in prompt engineering and building vector databases.
- Experience in implementing RAG use cases and chatbot solutions.
- Experience with various AI models, including GPT, Llama, and Hugging Face.
- Proficiency in using AWS Bedrock and hosting AI solutions on AWS.
- Experience with implementing AI projects, including Proof of Concepts (POCs).
- Familiarity with LangChain, LangGraph, and AutoGen.
- Excellent communication skills and ability to work collaboratively in a team environment.
- Demonstrated ability to take ownership and drive projects to completion.
Beneficial Skills and Experience:
- Experience with containerization and orchestration tools (Docker, Kubernetes).
- Familiarity with data visualization tools and techniques.
- Knowledge of big data technologies (Spark, Hadoop).
- Experience with version control systems (Git).
- Understanding of data governance and security best practices.
- Experience with monitoring and logging tools (Prometheus, Grafana).
- Stakeholder management skills and ability to communicate technical concepts to non-technical audiences.