Solutions Engineer

• 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

Communication skills Sales enablement Kubernetes NoSQL, * 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