AI Solutions Architect

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with technical leaders, stakeholders, and strategic partners to facilitate the implementation of Graph+GenAI solutions.

• Act as a trusted advisor and thought partner for decision-makers during complex, high-impact projects.

• Design and advocate for resilient, scalable solution architectures.

• Oversee the deployment of Graph+GenAI systems that align with enterprise needs and industry best practices.

• Work with customer leadership to grasp strategic goals and convert them into AI solutions utilizing graph databases and LLMs.

• Drive requirements discovery, evaluate enterprise data ecosystems, and identify opportunities to scale graph-based AI applications.

• Manage stakeholder engagement to direct project scope, prioritize tasks, mitigate risks, and ensure projects are completed on time.

• Develop, test, and launch production-ready AI applications that integrate graph databases with LLMs and orchestration frameworks.

• Write production-level code while optimizing applications for performance, scalability, and integration with customer systems.

• Continuously assess and enhance deployed AI applications.

• Collaborate with Product and Marketing teams to influence the roadmap and share field insights.

• Compile approaches, best practices, and lessons learned into thought leadership, methodologies, and published materials.

• Share knowledge through workshops, training sessions, and documentation.

• Commit to continuous learning and remain updated on the evolving landscape of GenAI.

⛳️ Requirements

• Over 5 years of experience in architecting and delivering enterprise-grade applications.

• In-depth understanding of the complete software development lifecycle.

• Experience working with Large Language Models, including prompt engineering, fine-tuning, and application integration.

• Current knowledge of various LLM providers, their strengths and weaknesses, as well as open-source LLMs.

• Advanced proficiency in at least one major programming language, such as Java, JavaScript, Python, or C#.

• Proven ability to deliver clean, maintainable, and scalable code within complex systems.

• Extensive hands-on experience with Linux, Docker, Kubernetes, and version control systems like Git or SVN.

• Expert-level proficiency with version control systems in enterprise development workflows.

• Demonstrated experience deploying and scaling applications on AWS, Azure, or GCP.

• Strategic understanding of cloud-native architecture and DevOps best practices.

• In-depth knowledge of generative AI frameworks, including LangChain, LlamaIndex, or Haystack.

• Familiarity with cloud-native AI platforms such as AWS Bedrock, Google Vertex AI, or Azure ML.

• Strong background in data engineering, analytics, or data science.

• Ability to design data pipelines and workflows across both structured and unstructured data.

• Hands-on experience with Hadoop, Spark, Hive, SQL, and NoSQL database systems.

• Deep expertise in graph data modeling and query languages like Cypher.

• Practical experience with graph databases such as Neo4j, Amazon Neptune, or TigerGraph, or triple stores like Ontotext or Stardog.

• Exceptional communication and stakeholder engagement skills.

• Ability to influence cross-functional teams and align technical decisions with business objectives.

• Strong analytical and problem-solving skills.

• Capability to architect AI solutions and mentor teams through the implementation process.

• Willingness and ability to travel up to 50%.

🏝️ Benefits

• Stock option grant.

• Annual bonus eligibility for certain roles.

• Medical benefits.

• Dental benefits.

• Vision benefits.

• 401(k) plan.

• Paid time off.

• Certain leaves of absence.

• An inclusive, diverse, and equitable workplace.

• Opportunity to influence the future of data and analytics.

• Customer-facing workshops, training, and professional development through ongoing learning.