Principal AI Solutions Architect

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

📋 Description

• Oversee the design, construction, and implementation of AI solutions that integrate graph databases and AI technologies.

• Serve as a trusted consultant to strategic clients on intricate data issues and business value propositions.

• Collaborate with technical leaders, stakeholders, and strategic partners to facilitate Graph+GenAI deployments.

• Design and promote robust, scalable architectures for enterprise solutions.

• Identify requirements, evaluate enterprise data ecosystems, and uncover graph-based AI opportunities.

• Lead stakeholder interactions to manage project scope, priorities, risks, delivery, and measurable business outcomes.

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

• Write production-quality code and optimize applications for performance, scalability, and seamless customer-system integration.

• Continuously assess and enhance deployed AI applications.

• Work closely with Product and Marketing teams to influence the product roadmap and consolidate field insights into thought leadership and methodologies.

• Conduct workshops, training sessions, and create documentation for internal teams and clients.

• Maintain ongoing education in the rapidly evolving GenAI landscape.

⛳️ Requirements

• Over 10 years of experience in architecting and delivering enterprise-level applications.

• Profound understanding of the entire software development lifecycle.

• At least 5 years of experience with Large Language Models, including prompt engineering, fine-tuning, and LLM integration.

• Current knowledge of LLM providers and open-source LLMs.

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

• Demonstrated history of delivering clean, maintainable, and scalable code.

• Practical deployment experience with Linux, Docker, and Kubernetes.

• Expert-level proficiency in version control systems like Git or SVN.

• Expertise in deploying and scaling applications on AWS, Azure, or GCP.

• Understanding of cloud-native architecture and DevOps best practices.

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

• Familiarity with AWS Bedrock, Google Vertex AI, or Azure ML.

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

• Capability to design data pipelines and workflows for 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 or triple stores, including Neo4j, Amazon Neptune, TigerGraph, Ontotext, or Stardog.

• Excellent communication and stakeholder engagement skills.

• Strong analytical and problem-solving capabilities.

• Willingness and ability to travel up to 50%.

• No specific educational qualifications are required.

🏝️ Benefits

• Stock option grant.

• Eligibility for annual bonuses for certain positions.

• Medical benefits.

• Dental benefits.

• Vision benefits.

• 401(k) plan.

• Paid time off.

• Various leaves of absence.

• An inclusive, diverse, and equitable workplace.

• Opportunities to influence the future of data and analytics.