AI Solutions Architect
New
N
Neo4jGraph databases and AI
Remote: United StatesFull-TimeSenior
SalaryAnnual On Target Earnings Range $160,000 — $220,000 USD
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Job Details
- Experience
- 5+ years of experience architecting and delivering enterprise-grade applications
- Required Skills
- DockerPythonJavaJavascriptKubernetesC#Prompt Engineering
Requirements
- 5+ years of experience architecting and delivering enterprise-grade applications.
- Deep understanding of the software development lifecycle and ability to guide complex design and implementation decisions.
- Experience with LLMs, including prompt engineering, fine-tuning, and integrating LLMs into applications.
- Advanced proficiency in at least one major programming language, such as Java, JavaScript, Python, or C#.
- Hands-on deployment experience with Linux, Docker, and Kubernetes, and expert-level use of version control systems such as Git or SVN.
- Expertise deploying and scaling applications on AWS, Azure, or GCP, with understanding of cloud-native architecture and DevOps best practices.
- Knowledge of generative AI frameworks such as LangChain, LlamaIndex, or Haystack, and cloud-native AI platforms such as AWS Bedrock, Google Vertex AI, or Azure ML.
- Background in data engineering, analytics, or data science, including designing data pipelines and workflows across structured and unstructured data.
- Hands-on experience with big data technologies such as Hadoop, Spark, or Hive, and SQL and NoSQL database systems.
- Expertise in graph data modeling and query languages such as Cypher, with practical experience in graph databases or triple stores.
- Strong communication and stakeholder engagement skills, with the ability to influence cross-functional teams and align technical decisions with business goals.
- Strong analytical and problem-solving abilities, including the ability to architect AI solutions and mentor teams through implementation.
- Willingness and ability to travel up to 50% to engage with customers and support project execution.
Responsibilities
- Engage with technical leaders, stakeholders, and strategic partners to guide Graph+GenAI implementations.
- Design scalable solution architectures aligned with enterprise requirements and industry best practices.
- Lead customer discovery, assess enterprise data ecosystems, and identify opportunities for graph-based AI.
- Align project scope and priorities with stakeholders, mitigate risks, and support timely delivery.
- Develop, test, and deploy production-ready AI applications integrating graph databases, LLMs, and orchestration frameworks.
- Write production-level code and optimize applications for performance, scalability, and integration with customer systems.
- Evaluate and improve deployed AI applications as techniques and technologies evolve.
- Work with Product and Marketing teams to share field insights and develop methodologies and published assets.
- Deliver customer workshops, training sessions, and documentation, and share expertise internally.
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