TigerGraph is a platform for advanced analytics and machine learning on connected data. TigerGraph's core technology is the only scalable graph database for the enterprise. Its proven technology supports fraud detection, customer 360, MDM, IoT, AI, and machine learning.

Fortune 500 organizations and the most innovative mid-size and startup companies choose TigerGraph to accelerate their analytics, AI, and machine learning: Seven out of the top ten global banks use TigerGraph for real-time fraud detection. Over 50 million patients receive care path recommendations to assist them on their wellness journey. 300 million consumers receive personalized offers with recommendation engines powered by TigerGraph.

TigerGraph reduces power outages by optimizing the energy infrastructure for 1 billion people.

Requirements

may apply. If the selected candidate is located near one of our company offices, the candidate will have a hybrid work arrangement (2-3 days in-office).

Bachelor’s degree in Computer Science or a related field 8 years of relevant experience Skills and Knowledge Deep, hands-on experience with one or more vector databases or similarity search libraries. Proven experience designing and working with any graph database and query languages like Cypher Solid understanding of distributed systems concepts: consensus, replication, sharding, and fault tolerance. Solid programming fundamentals; experienced with C++, Go, or any other major programming language.

Understanding of distributed systems principles and the ability to evaluate trade-offs in system design. Familiar with Kafka, ETCD or similar technologies; Proactive and collaborative team player with strong communication skills. Open to adopting AI-assisted engineering practices ("vibe coding") to improve productivity and code quality.

Bonus Points Familiar with container tools such as Docker. Hands-on experience with gRPC or REST APIs. Passionate about systems performance profiling, tuning, or debugging.

Responsibilities

Lead the architecture, design, and evolution of highly available, scalable, and fault-tolerant distributed systems for graph data. Drive the optimization of data ingestion, indexing, and query pipelines, leading performance analysis and scalability improvements for low-latency, high-throughput workloads. Lead the diagnosis and resolution of complex production issues, driving root cause analysis, operational improvements, and preventive engineering practices.

Provide technical leadership through design reviews, code reviews, mentoring, and driving engineering best practices across the team.

as required.

Software Engineer