Experience: Minimum 6+ years
Required skills: Java or Phyton with GenAI / LLMs (RAG, Agentic systems), Microsoft Copilot
Nice to have skills: NodeJS, Document AI, Intelligent Document Processing (IDP), Optical Character Recognition (OCR), Natural Language Processing (NLP), and Virtual Assistants such as Kore.ai and similar platforms.
Job Summary:
Software Engineer (GenAI) will design and deliver robust enterprise applications using Java, Spring and Microservices within a hybrid work model. Strong in Java or Phyton with GenAI / LLMs (RAG, Agentic systems), Microsoft Copilot
Responsibilities:
- Design and implement scalable microservices using Java, Spring Boot and Spring MVC to support high volume cards and payments processing in a hybrid work environment.
- Develop secure and efficient APIs for authorizing clearing and settling card transactions while maintaining strict compliance with industry standards for data protection.
- Optimize application performance and scalability by profiling services tuning JVM parameters and refining database interactions for peak transaction windows in day shift operations.
- Collaborate with product owners architects and quality engineers to refine user stories and transform complex payments requirements into clear technical designs.
- Implement robust error handling logging and monitoring strategies that provide deep observability into microservices health transaction flows and exception patterns.
- Write clean modular and testable Java and JavaScript code with high unit and integration test coverage to ensure reliability of cards and payments features.
- Integrate applications with card networks payment gateways and internal risk systems while ensuring accurate message formats and stable connectivity.
- Conduct detailed code reviews and provide constructive feedback that improves code quality security posture and adherence to engineering standards across the team.
- Coordinate with DevOps teams to containerize services configure pipelines and support smooth deployments across multiple test and production environments.
- Analyze production incidents in cards and payments flows identify root causes and implement permanent fixes that enhance stability and customer trust.
- Document technical designs sequence diagrams and interface contracts so that other engineers and partner teams can understand and extend the platform with confidence.
- Mentor less experienced engineers through pairing design discussions and example implementations that demonstrate modern patterns for microservices and transaction processing.
- Engage with business and operations stakeholders to clarify acceptance criteria refine edge cases and ensure that delivered features reduce friction for payment users.
Qualifications:
- Demonstrate strong proficiency in Java and object oriented design principles applied to complex transaction processing systems in the cards and payments domain.
- Exhibit deep hands on experience building and maintaining microservices using Spring Boot and Spring MVC with a focus on reliability and observability.
- Apply solid skills in JavaScript for building or enhancing user facing components and internal tools that interact with payments services.
- Bring proven experience in cards and payments including authorization flows settlement cycles chargebacks and fraud controls in regulated environments.
- Utilize practical knowledge of relational databases messaging systems and caching strategies to support low latency and high throughput payment workloads.
- Show familiarity with testing frameworks continuous integration practices and code quality tools that ensure safe and repeatable releases.
关于高知特 (Cognizant)
高知特(Cognizant)(纳斯达克代码:CTSH)作为一家AI Builder和相关技术服务提供商,致力于通过打造全栈AI解决方案,帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长,将企业独特的业务场景融入科技系统,赋能组织释放人才潜能,推动切实成果,并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情,敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外,候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
Cognizant 是一家提供平等就业机会的雇主。在招聘过程中,您的申请和候选资格不会因种族、肤色、性别、宗教、信仰、性取向、性别认同、国籍、残疾、遗传信息、怀孕、退伍军人身份或任何其他受联邦、州或地方法律保护的特征而受到影响。







