MySignature

• Design, build, and evolve modern, cloud-native fullstack systems across frontend, backend, and infrastructure layers. • Architect and implement scalable RESTful APIs and event-driven backend services that integrate with internal systems and third-party platforms. • Build and maintain mature React and TypeScript frontend applications with a strong focus on usability, performance, accessibility, and maintainability. • Own features end-to-end, including discovery, requirements clarification, technical design, implementation, testing, deployment, and post-release iteration. • Make sound architectural decisions and clearly communicate technical tradeoffs to stakeholders. • Design and optimize relational and/or NoSQL data models to support scalability, reliability, and performance. • Contribute to and improve CI/CD pipelines and release processes to enable frequent, reliable deployments. • Diagnose, resolve, and prevent production issues through strong observability, monitoring, and root cause analysis practices. • Champion engineering best practices, including testing strategy, code quality, documentation, and maintainable design patterns. • Mentor other engineers through code reviews, knowledge sharing, and technical guidance.

• Perform deep-dive analysis into existing system architecture, data models, workflows, and integrations across the product ecosystem, particularly in Salesforce • Document current-state processes, data flows, and system interactions, identifying gaps, redundancies, and manual workarounds • Elicit and document business, functional, and non-functional requirements from stakeholders across Product, Engineering, Operations, Sales, and Marketing • Translate complex technical and operational findings into clear documentation, diagrams, and recommendations that can be consumed by both technical and non-technical audiences • Surface automation and integration opportunities that align to product strategy and roadmap priorities. • Identify integration opportunities between systems to improve data consistency, scalability, and operational efficiency • Support evaluation of how existing tools and platforms (e.g., CRM, marketing automation, contract management, analytics, portals) can be better leveraged to solve business problems • Work collaboratively in our product operating model in which we enable continuous discovery and delivery of solutions that achieve meaningful customer and business outcomes. • Own the product and integration strategy for the systems and workflows you analyze • Partner with Engineering to shape solutions, define scope, and make tradeoff decisions • Convert discovery outputs into well-defined backlogs, acceptance criteria, and delivery plans • Drive alignment across stakeholders on priorities, timelines, and expected outcomes • Assist in defining success metrics and validating that delivered solutions address the originally identified gaps • Serve as a connective layer between business needs, product strategy, and technical execution • Support ongoing product operations through QA testing, troubleshooting, and hands on assistance for users

• Work with other teams across CoreTrust to develop key metrics to achieve business outcomes. • Work cross functionally to translate business problems into solutions that can be solved and informed by data and automated with AI Agents. • Have curiosity and apply analytical skills to dive deep into data to find key insights that impact the business. • Develop models of usage, user behavior & business behavior to make recommendations and influence the product road map. • Be a champion of AB testing. Design, execute and analyze experiments to prove product change attribution. • Utilize tools like SQL, Python, LLMs and platforms like Azure AI Foundry or Amazon Bedrock to execute analysis and create AI applications. • Track and monitor projects in JIRA. • Design, implement, and maintain analytics, models and LLM-driven scripts/software. • Work with stakeholders across the organization to understand requirements and generate actionable insights. • Work as part of a team to maintain a high-quality data lake house. • Serve as a subject matter expert on machine learning, AI agents, and statistics. • Be part of the Data Science Team to share ideas and best practices. • Create dashboards and reports to clearly and concisely communicate results and insights.