Sales Engineering Tech

Sales Engineer
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. TigerGraph reduces power outages by optimizing the energy infrastructure for 1 billion people.
As a Sales Engineer, you are the primary technical advisor to prospective customers throughout the sales cycle. You'll partner with Sales Directors to uncover customer challenges, demonstrate TigerGraph's value, and guide opportunities from discovery through technical validation to close. Partner with Sales Directors on account strategy, territory planning, and opportunity qualification to drive new business and expansion.
Lead technical discovery to understand customer objectives, architectures, and pain points, and translate them into use cases and solution designs.
Position TigerGraph against other graph databases, relational databases, and data platforms, and resolve technical objections.
Build relationships with technical champions, influencers, and decision-makers.
Keep internal teams informed on evaluation progress and risks, and hand off smoothly to Customer Success, Professional Services, and partners.
Share customer feedback and competitive intelligence with Product and Sales Leadership.
Support field marketing events and webinars, and contribute reusable demos and pre-sales collateral.
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience.
5+ years in enterprise software pre-sales, solutions consulting, or a similar customer-facing technical role, with success in complex sales cycles.
Strong SQL and working knowledge of Python or a similar language.
Solid understanding of relational, NoSQL, and graph databases; data modeling and integration (ETL/ELT); Working knowledge of AWS, Azure, and GCP.
Experience designing and validating solution architectures for SaaS, cloud, or on-premises deployments.
Experience with graph analytics, connected data, or graph-based use cases.
Strong communication, a consultative approach, and the ownership to manage evaluations, risks, and next steps independently.
Comfortable collaborating across a distributed team and traveling up to 30%.