• Pair directly with the founder to understand the platform, codebase, agentic development process, and intended product behavior. • Review AI/agent-generated code for modularity, maintainability, hidden fragility, silent failures, and poor integration boundaries. • Build automated test coverage around high-risk workflows, cross-portal user journeys, permissions, integrations, data persistence, and API failure modes. • Implement Playwright/API-level test automation, test data setup, CI checks, and failure artifacts such as traces, screenshots, and logs. • Improve dev/staging environment practices, CI/CD workflows, release checks, and monitoring feedback loops. • Use AI tools to accelerate test creation, bug reproduction, code review, and remediation while maintaining engineering discipline. • Create a prioritized backlog of technical hardening, test expansion, refactoring, and automation opportunities.

• Conducting requirements gathering and analysis to understand the domain of the software problem and/or functionality, the interfaces between hardware and software, and the overall software characteristics • Using programming, scripting, and/or database languages to write the software code • Supporting software testing, deployment, maintenance, and evolution activities by correcting programming errors, responding to scope changes, and coding software enhancements • Applying knowledge of software development best practices, including coding standards, code reviews, source control management, build processes, testing, and operations

• Define and drive the architecture of scalable, event-driven systems on AWS • Lead the design and evolution of core platform services and distributed systems • Set technical direction across teams, ensuring consistency and long-term maintainability • Solve complex, cross-cutting engineering problems (e.g. scaling, data consistency, system resilience) • Establish best practices for reliability, observability, and performance across the platform • Design systems that handle high event throughput, failure scenarios, and eventual consistency at scale • Partner closely with Data Engineering to shape data architecture, pipelines, and platform capabilities • Influence and improve engineering standards, tooling, and ways of working • Mentor senior engineers and act as a technical leader across multiple teams • Contribute to strategic technical decisions and roadmap planning

• The candidate will be responsible for the configuration and delivery of client-facing applications. • The candidate may assist with support for the development of process enhancements under the guidance of the Sr. Software Engineer and the Manager, Technical Operations. • Responsibilities will also include day-to-day maintenance of the health care application systems in operation, including tasks related to identifying and troubleshooting application issues and issues resolution or escalation, root cause analysis, manage communication and client relationship management in partnership with Infrastructure Service Support team members. • Prepare, transform, and structure client‑specific data exactly as per requirements gathered by Engagement and Product teams, while adhering to Medical, Legal, and Regulatory (MLR) guidelines. • Design, generate, and maintain baseline and customised messaging datasets (categories, key messages, content, footnotes, metadata) used across IVA client demos, frameworks, and productions. • Process and integrate data received from multiple third‑party vendors per client, applying business logic and transformation rules to produce client‑ready datasets. • Represent the Data Operations / Data Engineering function on all active client and product initiatives. • Participate in daily data operations and development stand‑up meetings to review data readiness, defects, transformations, and deployments. • Follow established change‑management procedures for data updates, transformations, and environment promotions. • Document and maintain data pipelines, transformation logic, and data standard operating procedures (SOPs). • Create and maintain WIKI articles for reusable data processes, transformation patterns, and troubleshooting guides. • Coordinate with Application Development, Product, and Front‑End teams to ensure data structures, tags (BR, span, classes), and attributes are optimized for UI rendering and configurability. • Support and execute data deployments across multiple environments (Development, UAT, Production) using Octopus Deploy and controlled release processes. • Manage and validate data flows from Goliath servers to Core servers and ultimately into Salesforce via stored procedures and Boomi ETL workflows. • Set up and maintain data configurations for new client implementations, including environment‑specific data variations and vendor inputs. • Assist in developing and maintaining automated data validation checks and regression test datasets to support future testing efforts. • Measure and track data‑related KPIs such as data quality metrics, transformation accuracy, defect leakage, re‑processing rates, and turnaround times. • Work closely with Product and Platform teams to support new data‑driven features, enhancements, and messaging capabilities. • Ensure all data changes align with defined lifecycle methodologies, auditability requirements, and risk guidelines. • Actively collaborate with end users, internal stakeholders, front‑end developers, external vendors, data analysts, and Engagement teams to resolve data issues and drive continuous improvement. • Contribute to the evolution of scalable, reusable data models and messaging frameworks across products.