Job Summary:
We’re looking for a Platform Engineer / Backend Engineer with extensive experience, strong Java, AWS and Kubernetes skills, and a strong engineering mindset to take a key role on our team. The engineer should have a thorough understanding of the Software Development Life Cycle (SDLC) and should have contributed across all its phases – requirements, design, development, testing, deployment and support – along with experience building scalable backend and cloud-native services. The role also calls for good experience using AI tools, including the ability to write the right prompts for a given context, to improve engineering productivity, documentation, testing and solution design. A good understanding of the Banking, Financial Services and Insurance (BFSI/BFS) domain is important so the engineer can write accurate, business-aware prompts and validate AI-assisted outputs in context.
Key Responsibilities:
Good understanding of design concepts, distributed systems and cloud-native architecture.
Bring a strong engineering mindset and a solid understanding of the Software Development Life Cycle (SDLC), with demonstrated contribution across all its phases – requirements analysis, design, development, testing, deployment and production support.
Maintain quality and ensure responsiveness, scalability and reliability of applications.
Experience with common design and architectural patterns coupled with a passion for writing clean, performant and well-tested code.
Maintain code integrity, organization and secure engineering practices.
Understand and implement security, data protection and compliance-aware development practices.
Develop backend services using Core Java 11 and above, JDBC, Microservices, REST Web Services, Spring Framework, Kafka and AWS.
Design, deploy and operate containerized services using Docker and Kubernetes, including AWS EKS/ECS, Helm or equivalent deployment tooling, service discovery, configuration, secrets and observability practices.
Use AI-assisted engineering tools responsibly for code generation, unit test creation, documentation, debugging, code review support, analysis and productivity improvement.
Write clear, accurate and context-rich prompts for AI tools by applying strong understanding of BFS/BFSI business processes, terminology, risk, controls and customer journeys.
Experience with cloud message APIs and usage of push notifications.
Follow and advocate best coding practices, CI/CD, continuous delivery and code reviews.
Experience working with relational and non-relational databases.
Essential Skills:Extensive experience in Java 11 and above, Spring Framework, MVC, JDBC, Hibernate, REST Microservices/API’s, Cloud API’s and AWS services such as Lambda, ECS, EKS and Terraform, with a strong engineering mindset.
Strong understanding of SDLC with demonstrated contribution across all its phases – requirements, design, development, testing, deployment and support.
Strong Kubernetes experience, including cluster concepts, deployments, services, ingress, config maps, secrets, autoscaling, monitoring/observability and troubleshooting containerized workloads.
Extensive experience in backend development using Oracle PL/SQL and NoSQL databases.
Good experience using AI tools in the software delivery lifecycle, including prompt writing, code assistance, test generation, documentation, debugging and validation of AI-generated outputs.
Good understanding of the BFS/BFSI domain, including financial products, customer/account journeys, regulatory sensitivity, data privacy, risk controls and domain terminology, to support accurate prompt engineering and business-context validation.
Nice to Have Skills:Good understanding of CI/CD framework and build automation.
Good understanding of Agile methodologies and practices.
Experience with infrastructure as code and deployment automation for Kubernetes-based platforms.
Analytical and reasoning skills.
Strong communication and collaboration skills.
Qualifications:
Expert in Core Java 11 and above.
Thorough understanding of Java EE architecture, design patterns and Spring Framework.
Experience writing RESTful web services.
Experience with commonly used AWS services such as Lambda, EKS, ECS and EC2.
Hands-on experience with Kubernetes, container orchestration and cloud-native deployment patterns.
Experience using AI tools for engineering productivity, prompt creation, documentation, testing and code analysis.
Good understanding of BFS/BFSI domain concepts to create business-aware prompts and review AI-assisted outputs for correctness.
Experience writing automation test scripts using Selenium / Cucumber.
Strong knowledge of SQL and RDBMS database design.
Experience as part of an Agile development team, preferably Scrum.
Extensive years of overall industry/software engineering experience, with a strong engineering mindset and contribution across all phases of the SDLC.
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。
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