• Designs, builds, tests, deploys, releases, and supports a regulated SaaS-based solution as part of a team • Provides innovative solutions to help resolve customer needs • Strives for continuous improvement and supports continuous integration, continuous development, and deployment pipelines • Identifies, encourages and builds automated processes; advocates for automation, continuous improvements and best practices • Participates in all phases of the solution lifecycle and works closely with a variety of internal, external business, and technology partners • Evaluates system and component releases for impact to business processes • Uses technical skills to code review, verify, and validate the software code developed • Gains knowledge of business processes and recognizes how individuals and technology can effectively support the success of business users • Collaborates with teams, mentors junior engineers, and ensures high-quality code and best practices are followed in a regulated software environment.

• Design & build distributed data systems – craft APIs, schemas, and replication paths that keep petabytes of workflow history durable and query-able. Clearly document design choices and operational knowledge to successfully deploy and run service with those features. • Drive reliability & performance – own SLOs, create chaos-test plans, profile hot paths, and lead incident reviews. • Technical leadership – break down roadmap epics, mentor mid-level engineers, steward design docs through RFC. • Cross-team collaboration – partner with the Server, Cloud, and DX teams to land features end-to-end.

• Develop and maintain robust, scalable web applications, working on both frontend and backend; • Integrate APIs and machine learning/AI models into applications; • Collaborate with data scientists, machine learning engineers, and other technical teams; • Contribute to the design and architecture of AI-based solutions; • Ensure good practices in coding, version control, testing, and documentation; • Explore and apply solutions based on generative AI, NLP, computer vision, or intelligent automation as required by the project.

• Architect and build low-latency systems operating at 1M+ QPS. • Design and deliver systems that let partners connect and run real-time workloads securely and efficiently. • Collaborate with partner engineering and product teams to plan, build, and launch integrations aligned with business and technical needs. • Own critical platform features from end-to-end, from design through rollout and adoption. • Proactively identify and resolve performance bottlenecks and scalability risks. • Set technical direction and guide implementation across the team. • Promote engineering quality through reviews, mentoring, and driving best practices in code, architecture, and platform design.