Cortracker Inc
AI Test Lead 100% Remote NOTES: Project Overview: TechEvo Application Modernization The Pitch: We are shifting our strategy from massive, slow application re-architectures to a highly targeted, AI-driven platform roadmap. Because bad actors are rapidly scaling AI models to find vulnerabilities, we need to stay ahead of the threat curve and "stop the bleeding." We are building internal AI agents to automate the modernization and security upgrades of our legacy applications. The Technical Scope The team is focused on two primary modernization tracks, utilizing Claude Code and Java: Track 1: Infrastructure & Core Tech Upgrades Migrating legacy applications running on older Linux platforms and older Java runtimes (e.g., upgrading from JDK 17 to JDK 25). Building AI agents that can scan and understand legacy applications, generate technical specifications, and automatically execute the dependency-by-dependency upgrades. Track 2: Security & Identity Modernization Transitioning applications from legacy security/authentication models (LDP, ISD) to modern Okta integration. Evaluating applications on a case-by-case basis to determine if they need a tech stack upgrade, a security upgrade, or both. The Role: Agentic Engineers We are not looking for standard developers to manually rewrite code. We are looking for Agentic Engineers. The Core Task: Write, instruct, and constantly refine AI agents/skills to handle the heavy lifting of modernizing our infrastructure stack. The Goal: Engineer the AI agents to successfully complete 90% of the upgrade work autonomously, leaving the remaining 10% for human verification and validation. The Ideal Candidate Profile Systems Thinkers: Must understand how massive enterprise systems interconnect. If they upgrade a database to a new server, they need to instantly understand the downstream impacts on connected systems. The "Fixers," Not The "Finders": We do not need auditors who simply identify vulnerabilities. We need hands-on engineers who build the automated solutions to fix them. Battle-Scarred Veterans: We are looking for engineers with real-world scars. A standard Senior Developer with 7 years of isolated coding experience will not survive here; they need a history of navigating complex, high-stakes system failures (P1 incidents). Quick Screening Questions for the Recruiter "Tell me about a time you had to modernize a legacy application. How did you map out the downstream impacts before making changes?" (Listen for systems thinking and architectural awareness, not just code-level changes). "How many P1 (Priority 1) incidents have you been involved in during your career, and what did they teach you about system design?" (Listen for battle scars and lessons learned). "If I asked you to automate a massive JDK upgrade across dozens of legacy applications today, how would you approach building an AI agent to do 90% of the work?" (Listen for an understanding of agentic engineering, automation, and prompt/skill design). ob Description Hands-on quality engineering lead or Senior AI Tester responsible for reverse-engineering application behavior, establishing missing system integration regression coverage, designing AI assisted test generation workflows and proving that agent driven modernization preserves functional, integration, security and operational behavior. Required Skills - 7-10 Years of QA/SDET/QE experience with strong automation and AI testing skills. • Good experience with AI Assisted QE, system integration testing. Strong SDET/quality engineering background with hands on automation of APIs, integrations, UI and end to end enterprise workflows. • Demonstrated use of AI/agentic tools to generate, refine, review, or maintain test scenarios and automation not merely general chatbot usage. • Experience creating regression, system integration coverage for applications with incomplete or outdated test suites. • Strong knowledge of test strategy, risk-based testing, test design, traceability, defect management, root-cause analysis and CI/CD quality gates. • Hands on experience with modern automation tools such as Playwright, Cypress, Selenium, REST/API automation, or equivalent; ability to choose tools based on architecture. • Working knowledge of Java/.NET application behavior, databases/SQL, APIs, middleware, authentication/authorization, and enterprise integration patterns. • Understanding of LDAP and token-based authentication concepts sufficient to design security and role/authorization test scenarios. • Ability to evaluate nondeterministic AI outputs with repeatable acceptance criteria, structured evaluation, and human verification. Job Responsibilities Job Duties - Assess each application's existing test assets, business-critical flows, integrations, data dependencies, security behavior and regression risk before modernization begins. • Reverse-engineer system behavior with developers and AI agents, then create a risk-based system integration and regression strategy where adequate suites do not already exist. • Design and build executable test suites in enterprise test management/automation tooling (for example Xray-style suites), beyond developer-only unit/JUnit coverage. • Create, refine and govern AI agents/skills that assist with test scenario generation, test data design, coverage analysis, traceability, defect triage and regression maintenance. • Define test coverage for runtime/framework upgrades, dependency changes, OS/middleware changes, database/integration impacts, and LDAP-to-Okta/token-based security changes. • Establish quality gates for agent-generated code and modernization changes, including functional, integration, API, security, negative, compatibility, performance-smoke and deployment validation as appropriate. • Lead testers embedded in delivery pods, assign test work, review automation, coach AI-assisted testing practices and remain hands on for complex flows. • Partner with Development Leads to ensure technical specifications are testable and that acceptance criteria include measurable verification and rollback conditions. • Integrate automated tests into CI/CD where feasible and provide rapid, trustworthy feedback on modernization changes. • Drive defect root cause analysis and distinguish application defects, environment issues, test data issues, dependency incompatibility and AI agent errors. • Track escaped defects, automation coverage, execution reliability, agent generated test quality, rework, and regression effectiveness; use findings to improve skills/agents. Job Requirements - 7-10 Years of QA/SDET/QE experience with strong automation and AI testing skills. • Good experience with AI Assisted QE, system integration testing. Role Purpose: Hands-on quality engineering lead or Senior AI Tester responsible for reverse-engineering application behavior, establishing missing system integration regression coverage, designing AI assisted test generation workflows and proving that agent driven modernization preserves functional, integration, security and operational behavior. Roles and Responsibilities: • 7-10 Years of QA/SDET/QE experience with strong automation and AI testing skills. • Good experience with AI Assisted QE, system integration testing. • Assess each application's existing test assets, business-critical flows, integrations, data dependencies, security behavior and regression risk before modernization begins. • Reverse-engineer system behavior with developers and AI agents, then create a risk-based system integration and regression strategy where adequate suites do not already exist. • Design and build executable test suites in enterprise test management/automation tooling (for example Xray-style suites), beyond developer-only unit/JUnit coverage. • Create, refine and govern AI agents/skills that assist with test scenario generation, test data design, coverage analysis, traceability, defect triage and regression maintenance. • Define test coverage for runtime/framework upgrades, dependency changes, OS/middleware changes, database/integration impacts, and LDAP-to-Okta/token-based security changes. • Establish quality gates for agent-generated code and modernization changes, including functional, integration, API, security, negative, compatibility, performance-smoke and deployment validation as appropriate. • Lead testers embedded in delivery pods, assign test work, review automation, coach AI-assisted testing practices and remain hands on for complex flows. • Partner with Development Leads to ensure technical specifications are testable and that acceptance criteria include measurable verification and rollback conditions. • Integrate automated tests into CI/CD where feasible and provide rapid, trustworthy feedback on modernization changes. • Drive defect root cause analysis and distinguish application defects, environment issues, test data issues, dependency incompatibility and AI agent errors. • Track escaped defects, automation coverage, execution reliability, agent generated test quality, rework, and regression effectiveness; use findings to improve skills/agents. Required Skills: • Strong SDET/quality engineering background with hands on automation of APIs, integrations, UI and end to end enterprise workflows. • Demonstrated use of AI/agentic tools to generate, refine, review, or maintain test scenarios and automation not merely general chatbot usage. • Experience creating regression, system integration coverage for applications with incomplete or outdated test suites. • Strong knowledge of test strategy, risk-based testing, test design, traceability, defect management, root-cause analysis and CI/CD quality gates. • Hands on experience with modern automation tools such as Playwright, Cypress, Selenium, REST/API automation, or equivalent; ability to choose tools based on architecture. • Working knowledge of Java/.NET application behavior, databases/SQL, APIs . click apply for full job details
AI Test Lead 100% Remote NOTES: Project Overview: TechEvo Application Modernization The Pitch: We are shifting our strategy from massive, slow application re-architectures to a highly targeted, AI-driven platform roadmap. Because bad actors are rapidly scaling AI models to find vulnerabilities, we need to stay ahead of the threat curve and "stop the bleeding." We are building internal AI agents to automate the modernization and security upgrades of our legacy applications. The Technical Scope The team is focused on two primary modernization tracks, utilizing Claude Code and Java: Track 1: Infrastructure & Core Tech Upgrades Migrating legacy applications running on older Linux platforms and older Java runtimes (e.g., upgrading from JDK 17 to JDK 25). Building AI agents that can scan and understand legacy applications, generate technical specifications, and automatically execute the dependency-by-dependency upgrades. Track 2: Security & Identity Modernization Transitioning applications from legacy security/authentication models (LDP, ISD) to modern Okta integration. Evaluating applications on a case-by-case basis to determine if they need a tech stack upgrade, a security upgrade, or both. The Role: Agentic Engineers We are not looking for standard developers to manually rewrite code. We are looking for Agentic Engineers. The Core Task: Write, instruct, and constantly refine AI agents/skills to handle the heavy lifting of modernizing our infrastructure stack. The Goal: Engineer the AI agents to successfully complete 90% of the upgrade work autonomously, leaving the remaining 10% for human verification and validation. The Ideal Candidate Profile Systems Thinkers: Must understand how massive enterprise systems interconnect. If they upgrade a database to a new server, they need to instantly understand the downstream impacts on connected systems. The "Fixers," Not The "Finders": We do not need auditors who simply identify vulnerabilities. We need hands-on engineers who build the automated solutions to fix them. Battle-Scarred Veterans: We are looking for engineers with real-world scars. A standard Senior Developer with 7 years of isolated coding experience will not survive here; they need a history of navigating complex, high-stakes system failures (P1 incidents). Quick Screening Questions for the Recruiter "Tell me about a time you had to modernize a legacy application. How did you map out the downstream impacts before making changes?" (Listen for systems thinking and architectural awareness, not just code-level changes). "How many P1 (Priority 1) incidents have you been involved in during your career, and what did they teach you about system design?" (Listen for battle scars and lessons learned). "If I asked you to automate a massive JDK upgrade across dozens of legacy applications today, how would you approach building an AI agent to do 90% of the work?" (Listen for an understanding of agentic engineering, automation, and prompt/skill design). ob Description Hands-on quality engineering lead or Senior AI Tester responsible for reverse-engineering application behavior, establishing missing system integration regression coverage, designing AI assisted test generation workflows and proving that agent driven modernization preserves functional, integration, security and operational behavior. Required Skills - 7-10 Years of QA/SDET/QE experience with strong automation and AI testing skills. • Good experience with AI Assisted QE, system integration testing. Strong SDET/quality engineering background with hands on automation of APIs, integrations, UI and end to end enterprise workflows. • Demonstrated use of AI/agentic tools to generate, refine, review, or maintain test scenarios and automation not merely general chatbot usage. • Experience creating regression, system integration coverage for applications with incomplete or outdated test suites. • Strong knowledge of test strategy, risk-based testing, test design, traceability, defect management, root-cause analysis and CI/CD quality gates. • Hands on experience with modern automation tools such as Playwright, Cypress, Selenium, REST/API automation, or equivalent; ability to choose tools based on architecture. • Working knowledge of Java/.NET application behavior, databases/SQL, APIs, middleware, authentication/authorization, and enterprise integration patterns. • Understanding of LDAP and token-based authentication concepts sufficient to design security and role/authorization test scenarios. • Ability to evaluate nondeterministic AI outputs with repeatable acceptance criteria, structured evaluation, and human verification. Job Responsibilities Job Duties - Assess each application's existing test assets, business-critical flows, integrations, data dependencies, security behavior and regression risk before modernization begins. • Reverse-engineer system behavior with developers and AI agents, then create a risk-based system integration and regression strategy where adequate suites do not already exist. • Design and build executable test suites in enterprise test management/automation tooling (for example Xray-style suites), beyond developer-only unit/JUnit coverage. • Create, refine and govern AI agents/skills that assist with test scenario generation, test data design, coverage analysis, traceability, defect triage and regression maintenance. • Define test coverage for runtime/framework upgrades, dependency changes, OS/middleware changes, database/integration impacts, and LDAP-to-Okta/token-based security changes. • Establish quality gates for agent-generated code and modernization changes, including functional, integration, API, security, negative, compatibility, performance-smoke and deployment validation as appropriate. • Lead testers embedded in delivery pods, assign test work, review automation, coach AI-assisted testing practices and remain hands on for complex flows. • Partner with Development Leads to ensure technical specifications are testable and that acceptance criteria include measurable verification and rollback conditions. • Integrate automated tests into CI/CD where feasible and provide rapid, trustworthy feedback on modernization changes. • Drive defect root cause analysis and distinguish application defects, environment issues, test data issues, dependency incompatibility and AI agent errors. • Track escaped defects, automation coverage, execution reliability, agent generated test quality, rework, and regression effectiveness; use findings to improve skills/agents. Job Requirements - 7-10 Years of QA/SDET/QE experience with strong automation and AI testing skills. • Good experience with AI Assisted QE, system integration testing. Role Purpose: Hands-on quality engineering lead or Senior AI Tester responsible for reverse-engineering application behavior, establishing missing system integration regression coverage, designing AI assisted test generation workflows and proving that agent driven modernization preserves functional, integration, security and operational behavior. Roles and Responsibilities: • 7-10 Years of QA/SDET/QE experience with strong automation and AI testing skills. • Good experience with AI Assisted QE, system integration testing. • Assess each application's existing test assets, business-critical flows, integrations, data dependencies, security behavior and regression risk before modernization begins. • Reverse-engineer system behavior with developers and AI agents, then create a risk-based system integration and regression strategy where adequate suites do not already exist. • Design and build executable test suites in enterprise test management/automation tooling (for example Xray-style suites), beyond developer-only unit/JUnit coverage. • Create, refine and govern AI agents/skills that assist with test scenario generation, test data design, coverage analysis, traceability, defect triage and regression maintenance. • Define test coverage for runtime/framework upgrades, dependency changes, OS/middleware changes, database/integration impacts, and LDAP-to-Okta/token-based security changes. • Establish quality gates for agent-generated code and modernization changes, including functional, integration, API, security, negative, compatibility, performance-smoke and deployment validation as appropriate. • Lead testers embedded in delivery pods, assign test work, review automation, coach AI-assisted testing practices and remain hands on for complex flows. • Partner with Development Leads to ensure technical specifications are testable and that acceptance criteria include measurable verification and rollback conditions. • Integrate automated tests into CI/CD where feasible and provide rapid, trustworthy feedback on modernization changes. • Drive defect root cause analysis and distinguish application defects, environment issues, test data issues, dependency incompatibility and AI agent errors. • Track escaped defects, automation coverage, execution reliability, agent generated test quality, rework, and regression effectiveness; use findings to improve skills/agents. Required Skills: • Strong SDET/quality engineering background with hands on automation of APIs, integrations, UI and end to end enterprise workflows. • Demonstrated use of AI/agentic tools to generate, refine, review, or maintain test scenarios and automation not merely general chatbot usage. • Experience creating regression, system integration coverage for applications with incomplete or outdated test suites. • Strong knowledge of test strategy, risk-based testing, test design, traceability, defect management, root-cause analysis and CI/CD quality gates. • Hands on experience with modern automation tools such as Playwright, Cypress, Selenium, REST/API automation, or equivalent; ability to choose tools based on architecture. • Working knowledge of Java/.NET application behavior, databases/SQL, APIs . click apply for full job details
Cortracker Inc
Dallas, Texas
Sr. Automation Engineer - Mobile Testing Texas (hybrid) Locations: Dallas, Austin or San Antonio, TX. On site interview required for final. USC or GC only looking for someone to come in with proper mobile automation engineer experience needs to have more than 4-5 years with pure automation on appium- if they know appium they will be able to test on both iOS and Android sits on top of selenium and mobile has it's own nuances. Usually someone with web experience struggle or abandon mobile prefers some Expresso, Xcui text (apples unit test/ tool), UItest for android testing specifically- this is a test Quality Automation Engineer III, you are our quality control anchor, ensuring every application is stable and built with integrity, caring, and excellence. In this senior, specialized role, you will take strategic ownership of the design, creation, and testing of native mobile applications. We are looking for a true mobile automation expert-someone who deeply understands that mobile automation has its own unique nuances, sits on top of Selenium architecture, and requires a dedicated mobile-first mindset where traditional web automation approaches often fall short. You will use your advanced problem-solving skills and senior leadership capabilities to ensure our applications perform optimally, driving technical excellence while thriving in a highly collaborative environment. What You'll Do: Architect & Scale Frameworks: Oversee, design, review, build, and deploy advanced test automation solutions and frameworks tailored specifically for native iOS, Android, and cross-platform web ecosystems. Lead Troubleshooting & Triage: Lead the root-cause analysis and triage of the most complex escalated mobile and web system issues, navigating build nuances, resolving defects, and implementing continuous process improvements. Mentor and Guide: Act as a technical lead, guiding and mentoring other Test Automation Engineers to ensure their scripts align with modern automation frameworks and industry best practices-bridging the gap for team members transitioning between web and mobile testing. Strategic Collaboration: Partner directly with product management, project management, development teams, and business stakeholders to define project, product, and testing objectives. Maintain Standards: Write and execute robust functional test cases as needed to ensure complete, flawless device matrix and web browser coverage. Live Our Values: Always take action using Integrity, Caring, and Excellence to achieve all-win outcomes. What You'll Need: Education: Bachelor's degree in a technical field or equivalent experience. Web Automation Core: Direct, hands-on experience and mastery of Selenium WebDriver for enterprise web automation framework design. Mobile Experience: 4+ years of pure mobile test automation experience (specifically handling cross-platform testing across both iOS and Android ecosystems). Core Mobile Tooling: Expert-level mastery of Appium (including a deep understanding of how it sits on top of Selenium and how to handle its unique mobile nuances). Native Frameworks: Direct, hands-on experience with native platform testing tools, specifically XCUITest (Apple's unit/UI test tool) and Espresso or UI Automator (for Android-specific testing). Development Skills: Strong technical development experience with Java and an expert-level understanding of Object-Oriented programming concepts. Backend Capabilities: Strong expertise with SQL queries to validate backend data integrity. Problem Solving: Expert knowledge of the role of Test Automation and Software Quality Assurance in the development process, with the ability to independently identify technical issues, environment misconfigurations, and application defects. Tools & Version Control: Demonstrated experience developing functional, load, and batch test automation solutions using a distributed version-control management system like Core GIT. Additional Preferred Skills: Testing Toolsets: Experience using automated testing tools like JUnit, TestNG, Cucumber, JMeter, or SoapUI. DevOps & CI/CD: Knowledge of mobile and web DevOps pipelines, including Jenkins, Maven, or mobile-specific build systems. Non-Functional Testing: Knowledge of Non-Functional Testing methodologies (Performance, Security, and Accessibility Testing).
Sr. Automation Engineer - Mobile Testing Texas (hybrid) Locations: Dallas, Austin or San Antonio, TX. On site interview required for final. USC or GC only looking for someone to come in with proper mobile automation engineer experience needs to have more than 4-5 years with pure automation on appium- if they know appium they will be able to test on both iOS and Android sits on top of selenium and mobile has it's own nuances. Usually someone with web experience struggle or abandon mobile prefers some Expresso, Xcui text (apples unit test/ tool), UItest for android testing specifically- this is a test Quality Automation Engineer III, you are our quality control anchor, ensuring every application is stable and built with integrity, caring, and excellence. In this senior, specialized role, you will take strategic ownership of the design, creation, and testing of native mobile applications. We are looking for a true mobile automation expert-someone who deeply understands that mobile automation has its own unique nuances, sits on top of Selenium architecture, and requires a dedicated mobile-first mindset where traditional web automation approaches often fall short. You will use your advanced problem-solving skills and senior leadership capabilities to ensure our applications perform optimally, driving technical excellence while thriving in a highly collaborative environment. What You'll Do: Architect & Scale Frameworks: Oversee, design, review, build, and deploy advanced test automation solutions and frameworks tailored specifically for native iOS, Android, and cross-platform web ecosystems. Lead Troubleshooting & Triage: Lead the root-cause analysis and triage of the most complex escalated mobile and web system issues, navigating build nuances, resolving defects, and implementing continuous process improvements. Mentor and Guide: Act as a technical lead, guiding and mentoring other Test Automation Engineers to ensure their scripts align with modern automation frameworks and industry best practices-bridging the gap for team members transitioning between web and mobile testing. Strategic Collaboration: Partner directly with product management, project management, development teams, and business stakeholders to define project, product, and testing objectives. Maintain Standards: Write and execute robust functional test cases as needed to ensure complete, flawless device matrix and web browser coverage. Live Our Values: Always take action using Integrity, Caring, and Excellence to achieve all-win outcomes. What You'll Need: Education: Bachelor's degree in a technical field or equivalent experience. Web Automation Core: Direct, hands-on experience and mastery of Selenium WebDriver for enterprise web automation framework design. Mobile Experience: 4+ years of pure mobile test automation experience (specifically handling cross-platform testing across both iOS and Android ecosystems). Core Mobile Tooling: Expert-level mastery of Appium (including a deep understanding of how it sits on top of Selenium and how to handle its unique mobile nuances). Native Frameworks: Direct, hands-on experience with native platform testing tools, specifically XCUITest (Apple's unit/UI test tool) and Espresso or UI Automator (for Android-specific testing). Development Skills: Strong technical development experience with Java and an expert-level understanding of Object-Oriented programming concepts. Backend Capabilities: Strong expertise with SQL queries to validate backend data integrity. Problem Solving: Expert knowledge of the role of Test Automation and Software Quality Assurance in the development process, with the ability to independently identify technical issues, environment misconfigurations, and application defects. Tools & Version Control: Demonstrated experience developing functional, load, and batch test automation solutions using a distributed version-control management system like Core GIT. Additional Preferred Skills: Testing Toolsets: Experience using automated testing tools like JUnit, TestNG, Cucumber, JMeter, or SoapUI. DevOps & CI/CD: Knowledge of mobile and web DevOps pipelines, including Jenkins, Maven, or mobile-specific build systems. Non-Functional Testing: Knowledge of Non-Functional Testing methodologies (Performance, Security, and Accessibility Testing).
Cortracker Inc
Oak Lawn, Illinois
AI Assisted Fullstack Java Engineer Chicago, IL (hybrid) - 2 days on site Working Style: Highly self-sufficient and hands-on. While they will drive the team forward, this is an individual contributor role, not a formal lead. Technical Stack MUST- Back end Java Required: Must have strong skills in Java (backend) and AI PLUS/preferred-React (frontend). Engineering Fundamentals: Must have a strong grasp of design patterns, the ability to take specifications and deliver a finished product, and the engineering maturity to evaluate the quality of AI-generated code. AI Expertise Mandatory AI Skills: The candidate must come in with existing AI development experience (specifically mentioning Claude or similar tools). Why it's crucial: The client has limited resources and AI licenses, so they cannot afford the overhead of training someone on AI from scratch. The engineer's job will be to help build out the company's AI competency. We are looking for a US based AI Assisted Full Stack Engineer with demonstrated experience leveraging AI assisted development tools, including Anthropic Claude and Cursor, to accelerate design, development, refactoring, and hardening of software components while maintaining high standards of quality, security, and maintainability. Required Skills - • Demonstrate effective and responsible use of AI assisted development tools (including Claude and Cursor) • Actively contribute across the full software development lifecycle, including design, development, refactoring, testing, and production hardening of Java and/or React based components. • Collaborate closely with product owners, architects, and engineering teams. • Participate fully in Agile ceremonies and delivery processes. Job Duties - Sr level Engineer who can guide team on approaches to take to build confidence on the artifacts built by Claude to making them high quality production ready assets. Job Requirements - US based AI Assisted Full Stack Engineer with demonstrated experience leveraging AI assisted development tools, including Anthropic Claude and Cursor, to accelerate design, development, refactoring, and hardening of software components while maintaining high standards of quality, security, and maintainability. The AI Engineer is expected to apply an experienced, production focused approach, using AI tools as accelerators-not replacements for engineering judgment-to deliver CNA approved code suitable for deployment into production environments. Job Responsibilities Job Requirements - US based AI Assisted Full Stack Engineer with demonstrated experience leveraging AI assisted development tools, including Anthropic Claude and Cursor, to accelerate design, development, refactoring, and hardening of software components while maintaining high standards of quality, security, and maintainability. The AI Engineer is expected to apply an experienced, production focused approach, using AI tools as accelerators-not replacements for engineering judgment-to deliver CNA approved code suitable for deployment into production environments. AI Assisted Full Stack Engineer The AI Assisted Full Stack Engineer shall: Be a senior, hands on engineer with prior experience delivering production systems in enterprise environments. Demonstrate effective and responsible use of AI assisted development tools (including Claude and Cursor) to: Accelerate development cycles Improve code quality and maintainability Reduce rework introduced during review, testing, and production readiness phases Actively contribute across the full software development lifecycle, including design, development, refactoring, testing, and production hardening of Java and/or React based components. Collaborate closely with CNA product owners, architects, and engineering teams. Participate fully in CNA Agile ceremonies and delivery processes. Follow CNA engineering, security, architecture, and operational standards at all times. Production Readiness and Quality Standards All code and artifacts delivered under this SOW must be production ready and adhere to CNA development and operational standards, including but not limited to: Secure coding and data protection practices Clean, readable, and maintainable code structure Appropriate error handling, logging, and resilience patterns Performance considerations appropriate to scale and usage Unit and/or component level test coverage aligned with CNA expectations Compatibility with CNA CI/CD pipelines, deployment standards, and operational monitoring AI assisted outputs must be fully understood, reviewed, and owned by the Supplier Personnel delivering the work. Responsible AI Usage Specifically, the AI Engineer shall: Use AI tools strictly as development accelerators, not as autonomous decision makers. Ensure no CNA confidential, proprietary, regulated, or sensitive data is exposed to external AI systems beyond what is explicitly approved by Client. Be able to explain, review, modify, and justify all AI assisted outputs. Document material design or implementation decisions where AI assisted approaches significantly influenced outcomes. Knowledge Transfer and Enablement Demonstrating effective, responsible usage of AI assisted development tools in day to day delivery. Sharing best practices for prompt engineering, iterative refinement, AI assisted refactoring, and quality assurance. Participating in knowledge transfer sessions, walkthroughs, or enablement discussions as requested by Client. Work related tasks may include, but are not limited to, the following activities: Collaborating with Client stakeholders to gather technical and functional inputs required for component delivery. Developing and executing delivery plans aligned with agreed scope and priorities. Designing, building, refactoring, and hardening Java and/or React based components using AI assisted techniques. Supporting and participating in code reviews, ensuring CNA quality and security standards are met. Providing regular status updates through CNA Agile ceremonies and weekly reporting. Demonstrating AI assisted development efficiencies and outcomes to Client stakeholders
AI Assisted Fullstack Java Engineer Chicago, IL (hybrid) - 2 days on site Working Style: Highly self-sufficient and hands-on. While they will drive the team forward, this is an individual contributor role, not a formal lead. Technical Stack MUST- Back end Java Required: Must have strong skills in Java (backend) and AI PLUS/preferred-React (frontend). Engineering Fundamentals: Must have a strong grasp of design patterns, the ability to take specifications and deliver a finished product, and the engineering maturity to evaluate the quality of AI-generated code. AI Expertise Mandatory AI Skills: The candidate must come in with existing AI development experience (specifically mentioning Claude or similar tools). Why it's crucial: The client has limited resources and AI licenses, so they cannot afford the overhead of training someone on AI from scratch. The engineer's job will be to help build out the company's AI competency. We are looking for a US based AI Assisted Full Stack Engineer with demonstrated experience leveraging AI assisted development tools, including Anthropic Claude and Cursor, to accelerate design, development, refactoring, and hardening of software components while maintaining high standards of quality, security, and maintainability. Required Skills - • Demonstrate effective and responsible use of AI assisted development tools (including Claude and Cursor) • Actively contribute across the full software development lifecycle, including design, development, refactoring, testing, and production hardening of Java and/or React based components. • Collaborate closely with product owners, architects, and engineering teams. • Participate fully in Agile ceremonies and delivery processes. Job Duties - Sr level Engineer who can guide team on approaches to take to build confidence on the artifacts built by Claude to making them high quality production ready assets. Job Requirements - US based AI Assisted Full Stack Engineer with demonstrated experience leveraging AI assisted development tools, including Anthropic Claude and Cursor, to accelerate design, development, refactoring, and hardening of software components while maintaining high standards of quality, security, and maintainability. The AI Engineer is expected to apply an experienced, production focused approach, using AI tools as accelerators-not replacements for engineering judgment-to deliver CNA approved code suitable for deployment into production environments. Job Responsibilities Job Requirements - US based AI Assisted Full Stack Engineer with demonstrated experience leveraging AI assisted development tools, including Anthropic Claude and Cursor, to accelerate design, development, refactoring, and hardening of software components while maintaining high standards of quality, security, and maintainability. The AI Engineer is expected to apply an experienced, production focused approach, using AI tools as accelerators-not replacements for engineering judgment-to deliver CNA approved code suitable for deployment into production environments. AI Assisted Full Stack Engineer The AI Assisted Full Stack Engineer shall: Be a senior, hands on engineer with prior experience delivering production systems in enterprise environments. Demonstrate effective and responsible use of AI assisted development tools (including Claude and Cursor) to: Accelerate development cycles Improve code quality and maintainability Reduce rework introduced during review, testing, and production readiness phases Actively contribute across the full software development lifecycle, including design, development, refactoring, testing, and production hardening of Java and/or React based components. Collaborate closely with CNA product owners, architects, and engineering teams. Participate fully in CNA Agile ceremonies and delivery processes. Follow CNA engineering, security, architecture, and operational standards at all times. Production Readiness and Quality Standards All code and artifacts delivered under this SOW must be production ready and adhere to CNA development and operational standards, including but not limited to: Secure coding and data protection practices Clean, readable, and maintainable code structure Appropriate error handling, logging, and resilience patterns Performance considerations appropriate to scale and usage Unit and/or component level test coverage aligned with CNA expectations Compatibility with CNA CI/CD pipelines, deployment standards, and operational monitoring AI assisted outputs must be fully understood, reviewed, and owned by the Supplier Personnel delivering the work. Responsible AI Usage Specifically, the AI Engineer shall: Use AI tools strictly as development accelerators, not as autonomous decision makers. Ensure no CNA confidential, proprietary, regulated, or sensitive data is exposed to external AI systems beyond what is explicitly approved by Client. Be able to explain, review, modify, and justify all AI assisted outputs. Document material design or implementation decisions where AI assisted approaches significantly influenced outcomes. Knowledge Transfer and Enablement Demonstrating effective, responsible usage of AI assisted development tools in day to day delivery. Sharing best practices for prompt engineering, iterative refinement, AI assisted refactoring, and quality assurance. Participating in knowledge transfer sessions, walkthroughs, or enablement discussions as requested by Client. Work related tasks may include, but are not limited to, the following activities: Collaborating with Client stakeholders to gather technical and functional inputs required for component delivery. Developing and executing delivery plans aligned with agreed scope and priorities. Designing, building, refactoring, and hardening Java and/or React based components using AI assisted techniques. Supporting and participating in code reviews, ensuring CNA quality and security standards are met. Providing regular status updates through CNA Agile ceremonies and weekly reporting. Demonstrating AI assisted development efficiencies and outcomes to Client stakeholders