Senior Solutions Engineer

Responsibilities We are seeking a talented and motivated Solutions Engineer to join our rapidly growing team This is a high-impact, customer-facing role that sits at the center of our AI implementation and sales process You’ll work closely with our delivery teams to configure solutions for both prospective and existing customers, applying equal parts technical expertise and relationship-building strength to drive successful engagements Lead technical discovery and demo conversations with prospective customers, shaping their understanding of our product and uncovering key requirements Deliver tailored product demonstrations and guide pre-sales scoping to align solutions with customer use cases Own the end-to-end implementation process, configuring new checks and workflows based on detailed business requirements Lead customer-facing technical sessions to surface requirements and inform implementation design Partner with Customer Success on implementation planning and share regular updates across new and ongoing projects Serve as a trusted technical expert throughout the sales and implementation cycle, addressing questions on product capabilities, integrations, API functionality, and deployment options Qualifications Proficiency in SQL and database systems (relational and NoSQL) Understanding of data pipelines and transformations (e.g., filtering, aggregation) Familiarity with CI/CD concepts, tooling, and workflow optimization Working knowledge of Python or TypeScript (both preferred) Proven ability to quickly learn new technologies and concepts 7+ years in a Solutions/Forward-Deployed Engineering, or related technical role Experience with serialized data (JSON, YAML) and strong REST API skills Experience with Databricks, including configuring and running jobs Strong communication skills, including explaining technical concepts to non-technical audiences Prior experience in a SaaS environment supporting sales or services teams Familiarity with building and deploying containerized code (Docker, Kubernetes) Background in asset management operations or financial services technology Knowledge of AWS services and deployments Experienced in building data pipelines using libraries such as Pandas and PySpark Experience building data visualizations using BI tools Comfortable working in fast-paced environments and meeting tight deadlines #J-18808-Ljbffr