• AI-Driven Test Design & Automation • Use AI tools to generate, review, and optimize automated test cases — replacing manual test authoring wherever possible and dramatically expanding coverage without proportional increases in effort. • Leverage AI-assisted analysis to understand code flow, component interactions, and edge cases, ensuring automation suites reflect real-world usage scenarios rather than just happy paths. • Build and maintain automation test suites across Mobile, Desktop, and Web platforms using frameworks such as Selenium, Appium, Cypress, Robot Framework, or Tricentis Tosca — augmented by AI to accelerate framework setup and test scaffolding. • Apply AI tools to identify gaps in existing test coverage, prioritize high-risk areas, and continuously improve the depth and reliability of automation suites. • AI-Augmented Bug Detection & Reporting • Use AI-powered analysis to investigate user problems, detect patterns in defect data, and surface systemic quality issues that manual review would miss. • Create and manage bug reporting with AI-assisted summarization and root cause categorization — reducing manual documentation effort while improving defect report quality. • Apply exploratory testing techniques enhanced by AI to uncover edge cases and unexpected behaviors beyond scripted test scenarios. • CI/CD Integration & Quality Gatekeeping • Integrate automated test suites into CI/CD pipelines; use AI tools to monitor test results, flag regressions, and recommend pipeline adjustments based on quality trends. • Serve as a steward of final software release quality — using AI-generated quality dashboards and trend analysis to inform go/no-go decisions with data rather than intuition. • Develop and maintain status reporting and informative dashboards on all testing activities, leveraging AI to automate report generation and surface meaningful insights. • Collaboration & Agile Participation • Participate in backlog refinement to help design test cases, checklists, and test plans — using AI to rapidly generate draft test scenarios from user stories and acceptance criteria. • Work with deployment teams to resolve issues, contribute to product design, and improve the testability of functional and non-functional requirements. • Manage technical communications across teams with a clear understanding of overall system behavior and quality standards. • Research test tools, methodologies, and AI-driven QA trends; continuously evaluate and adopt emerging capabilities that improve team efficiency and product quality. • API & Advanced Testing • Apply advanced API testing skills using Postman or similar frameworks; use AI to generate and validate API test scenarios from specifications. • Leverage BDD principles and AI-assisted scenario generation to align automated tests with business intent and customer outcomes. • Conduct ad hoc and SQL-based testing as needed to validate data integrity and application behavior.

• Embed with non-technical stakeholders across Operations, Finance, Marketing, Customer Success, and other functions to understand their workflows in depth. • Surface the highest-impact automation opportunities and translate fuzzy, ambiguous problems into clear technical solutions. • Leave every stakeholder conversation with a sharper problem definition than you walked in with. • Build automations and internal tools using AI-native platforms, scripting, APIs, and whatever else gets the job done, pragmatism over purity. • Ship working v1s quickly so stakeholders can validate value before investment scales. • Wire together LLMs, agents, RAG patterns, and prompt design with existing systems to deliver real workflow outcomes. • Take working prototypes and harden them with the reliability, observability, error handling, and reusability needed for production use. • Define when a one-off solution is good enough as-is versus when it needs to be promoted into something the whole org can rely on. • Build the monitoring and documentation that lets automations run unattended and recover gracefully when they don't. • Coach and advise non-technical colleagues who are building their own automations: review their work, unblock them, and level up their skills over time. • Run lightweight enablement (working sessions, office hours, shared documentation) that grows the citizen-developer community at Later. • Communicate technical tradeoffs clearly to non-technical audiences and teach others to fish.

• Perform hands-on coding, scripting, and software development across multiple programming languages to support ICAM modernization initiatives. • Design, develop, test, and maintain automation scripts and pipelines that streamline ICAM processes, upgrades, and deployments. • Apply AI and machine learning techniques to enhance ICAM capabilities, including anomaly detection, adaptive authentication, and identity analytics. • Lead and contribute to ICAM modernization planning, roadmap development, and technical upgrade activities aligned with federal standards and best practices. • Collaborate with cross-functional teams including security engineers, architects, and system administrators to integrate ICAM solutions into existing enterprise environments. • Evaluate and implement industry best practices and emerging technologies related to identity management, access control, and zero trust architecture. • Develop and maintain technical documentation including design documents, runbooks, and standard operating procedures (SOPs). • Assist in the configuration and management of identity providers (IdPs), access management platforms, and directory services. • Support testing and validation activities including unit testing, integration testing, and system-level testing of ICAM components. • Provide technical guidance and mentorship to junior team members on ICAM concepts, AI tooling, and automation frameworks. • Interact daily with stakeholders to gather requirements, present solutions, and communicate technical findings in a clear and concise manner. • Operate within an Agile development environment while meeting government project milestones and deliverables.

• Design, build and deploy production-ready AI automations and intelligent workflows. • Develop and maintain multi-agent systems using modern AI orchestration frameworks. • Build LLM-powered business solutions using today's leading AI technologies. • Integrate AI agents with APIs, CRM platforms, messaging platforms, document generation tools and other business systems. • Deploy, monitor and maintain secure AI environments using Docker and modern deployment practices. • Debug, optimise and continuously improve AI workflows following deployment. • Work closely with business stakeholders to scope new automation opportunities and estimate technical effort. • Evaluate emerging AI technologies and recommend solutions that improve business efficiency. • Deliver scalable, reliable and maintainable AI solutions.