Generative Ai Engineer
1 week ago
**About Us**:
We are at the forefront of AI-driven transformation, leveraging cutting-edge technologies to build innovative, scalable, and efficient solutions. We are seeking a Generative AI Engineer who is passionate about integrating advanced AI capabilities to meet evolving business needs. If you have a strong technical background, hands-on experience in Python programming, and expertise in cloud platforms—especially AWS—this role is for you
**Key Responsibilities**:
**Generative AI Development**:
- Develop, test, and deploy Generative AI models using LangChain, AWS Bedrock, and other AI frameworks.
- Design and implement effective prompts to optimize AI-generated outcomes through prompt engineering.
**Vector Databases & RAG**:
- Leverage Vector Databases (e.g., AlloyDB, Aurora PostgreSQL DB) to enhance AI search efficiency and retrieval-augmented generation (RAG) for improved contextual responses.
- Implement advanced search and retrieval techniques, including code ingestion and knowledge retrieval, to enhance AI performance.
**Cloud Integration & Debugging**:
- Debug AI models and cloud-based solutions independently, particularly within AWS environments.
**End-to-End Application Development**:
**Cross-functional Collaboration & Communication**:
- Collaborate with cross-functional teams to test AI-driven solutions, gather feedback, and enhance system capabilities.
- Communicate complex AI concepts effectively to non-technical stakeholders, ensuring clarity in AI adoption and implementation.
**Innovation & Continuous Improvement**:
- Actively contribute to team discussions, providing insights and proposing solutions to AI-related challenges.
- Stay updated with the latest advancements in Generative AI and cloud-based AI solutions.
**Key Qualifications**:
**Proficiency in Python**:
- Strong programming skills, particularly in AI/ML model development, API integration, and cloud-based deployment.
**Prompt Engineering Expertise**:
- Ability to craft, test, and optimize AI prompts to enhance LLM (Large Language Model) performance.
**Experience with Vector Databases**:
- Hands-on knowledge of Vector Databases (e.g., AlloyDB, Aurora PostgreSQL DB) and retrieval-augmented generation (RAG) techniques.
**Preferred Qualifications**:
**AWS Cloud Certification**:
- Certifications such as AWS Certified Machine Learning or AWS Certified Solutions Architect are highly desirable.
**Multi-Language Proficiency**:
- Exposure to additional programming languages such as Java, React, and Angular.
**Awareness of Emerging AI Trends**:
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