AI Solutions Architect

Responsibilities

• Solution Architecting:
• Partner with customer technical leads, customer executives, and partners to manage and deliver successful implementations of Graph+GenAI solutions becoming a trusted advisor to decision-makers throughout the engagement.
• Propose solution architectures and manage the deployment of Graph+GenAI solutions according to complex customer requirements and implementation best practices.
• Interact with customer stakeholders to manage project scope, priorities, deliverables, risks and issues, and timelines for successful customer outcomes.
• Solution Engineering
• Develop, test, and deploy production-ready AI applications that integrate graph databases with LLMs and orchestration frameworks. This involves writing production-level code, optimising for performance and scalability, and ensuring seamless integration with customer systems.
• Continuously evaluate and improve the performance, scalability, and efficiency of deployed AI applications, incorporating new techniques and technologies as they emerge.
• Education & Enablement
• Collaborate with other teams at Neo4j (Product and Marketing) to influence the roadmap and provide insights from the field, and package approaches, best practices, and lessons learned into thought leadership, methodologies, and published assets.
• Share your expertise internally with other Neo4j teams and also with customers through workshops, training sessions, and documentation to empower them to effectively utilise, maintain, and reproduce the AI solutions you deliver.
• Maintain continuous learning and stay up-to-date with the rapidly evolving GenAI landscape, proactively seeking knowledge of new trends and technologies.
• Required Qualifications
• Enterprise Application Development: 5+ years of experience in designing and developing enterprise-class applications, demonstrating a strong understanding of software development lifecycle principles.
• Programming Proficiency: Competence and hands-on experience in at least one of the following languages: Java, JavaScript, Python, or C#. Ability to write clean, maintainable, and efficient code is essential.
• Deployment and Version Control: Hands-on experience with deployment software on major platforms, such as Linux, Docker, and Kubernetes, and proficiency in source control software, including Git and SVN.
• Cloud Computing Expertise: Practical experience with cloud platforms (e.g., AWS, Azure, GCP) and demonstrated proficiency in deploying applications within cloud environments.
• Generative AI Ecosystem Knowledge: Deep understanding of the generative AI ecosystem, including AI orchestration frameworks (e.g., LangChain, Llama Index, Haystack) and cloud provider AI offerings (e.g., AWS Bedrock, Vertex AI, Azure Machine Learning).
• Data Expertise: Strong foundation in data engineering, data analytics, or data science, with the ability to work effectively with various data types and sources. Experience using big data technologies (e.g. Hadoop, Spark, Hive) and database management systems (e.g. SQL and NoSQL).
• Graph Database Expertise

Benefits

Additional Information

About Neo4j: Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems. It includes enterprise-ready knowledge graphs for accurate, explainable, and governed AI; the most comprehensive, trusted, and easy-to-deploy graph capabilities across any environment and data source; and an unmatched ecosystem trusted by 84 of the Fortune 100 and supported by the world's largest graph community. Intelligence that works. Results that matter. Built to work everywhere and integrate with everything across every cloud for dynamic, personalized, and autonomous AI systems. We deliver quicker results, contextual knowledge, and solutions that impact customers and employees across the business. Our Vision: At Neo4j, we have always strived to help the world make sense of data. As business, society and knowledge become increasingly connected, our technology promotes innovation by helping organizations to find and understand data relationships. We created, drive and lead the graph database category, and we're disrupting how organizations leverage their data to innovate and stay competitive.

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