AI Solutions Architect
Skills
- Enterprise-level application development and software lifecycle knowledge.
- Proficiency with Large Language Models including prompt engineering and integration.
- Strong programming skills in Java, JavaScript, Python, or C#.
- Experience with deployment platforms including Linux, Docker, Kubernetes and version control using Git or SVN.
- Cloud computing and deployment experience with AWS, Azure, or GCP.
- Deep understanding of generative AI orchestration frameworks like LangChain and Llama Index.
- Solid expertise in graph database technology, data modeling, and query languages like Cypher.
- Excellent communication and collaboration skills.
- Problem-solving and analytical thinking to design effective AI solutions.
Responsibilities
- Collaborate with customer technical leads and executives to architect and deliver Graph+Generative AI solutions aligned with business needs.
- Develop, test, and deploy production-grade AI applications integrating graph databases with LLMs and orchestration frameworks.
- Manage project scope, timelines, risks, and customer communications for successful implementations.
- Partner with Neo4j cloud partners to provide joint consulting and technical guidance.
- Contribute insights to Neo4j product and marketing teams influencing roadmap and best practices.
- Deliver workshops, trainings, and documentation to empower customers and internal teams.
- Continuously update knowledge of Generative AI technologies and ecosystem developments.
Education
- Formal education in computer science, engineering, data science or related technical field preferred.
Benefits
- Medical, dental, and vision insurance.
- 401(k) retirement plan.
- Paid time off and various leaves of absence.
- Stock option grants and eligibility for annual bonuses.
- Opportunities for continuous learning and professional development.
Average salary estimate
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