• Design, build, and maintain scalable infrastructure for data engineering and analytics workloads in Databricks and Azure • Collaborate with data scientists, platform engineers, and DevOps to enable seamless integration between Databricks, data lakes, and other cloud services • Implement and manage CI/CD pipelines, infrastructure as code (Pulumi) and monitoring systems to support data platform operations • Drive improvements in security, observability, and automation for Azure and Databricks clusters, jobs, and user environments • Mentor junior engineers and contribute to infrastructure best practices, documentation, and internal tooling development

• Responsible for designing and creating engineering specifications for software applications and programs. • Responsible for designing & writing code that adheres to coding standards. • Performs code reviews. • Responsible for idea generation, exploring and implementing appropriate technical solutions to achieve the required product features. • Monitor technical process against project plan while safeguarding functionality, scalability and performance. • A part of an agile work team and participating in all scrum ceremonies, assisting in sprint planning and completing required sprints.

• Own product features end to end - design, build, test, deploy, and support features across both the Angular front end and the C#/.NET back end, taking responsibility for the complete user experience. • Build exceptional client experiences - create performant, accessible, and intuitive interfaces that help customers confidently work with complex financial data, from dashboards and visualizations to onboarding and transaction workflows. • Design and evolve APIs - build reliable, well-documented REST APIs and data contracts that are secure, scalable, backwards compatible, and easy for internal and external consumers to integrate with. • Write production-quality software - contribute clean, maintainable, well-tested code while continuously improving architecture, performance, reliability, and operational excellence. • Collaborate across disciplines - partner closely with Product Managers, Product Designers, QA, Data Science, and fellow engineers to translate business problems into technical solutions that deliver measurable customer value. • Own production outcomes - monitor, troubleshoot, and improve the systems you build using observability tools, testing, and continuous delivery practices to ensure a reliable customer experience. • Raise the engineering bar - provide thoughtful code reviews, mentor other developers, share technical knowledge, and help improve engineering standards across the team. • Leverage AI as a force multiplier - use AI-assisted development to accelerate implementation while applying sound engineering judgment, thoughtful system design, and strong problem framing to deliver the right solutions.

• Design and develop conversational AI solutions using enterprise platforms (Soundhound Amelia) • Build and maintain integrations between IVA platforms and backend systems using RESTful APIs and microservices • Collaborate with business stakeholders to gather requirements and translate them into technical specifications • Implement NLU training strategies, intent management, and dialog flow optimization • Write clean, maintainable code following object-oriented programming principles • Track and manage work items using Atlassian Jira and Agile methodologies • Stay current with emerging trends in conversational AI