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.
Acerca de Cognizant
Cognizant (Nasdaq: CTSH) es un creador de soluciones de IA y proveedor de servicios tecnológicos que conecta la inversión en IA con el valor empresarial mediante el desarrollo de soluciones de IA full‑stack para sus clientes. Su profundo conocimiento de la industria, junto con su experiencia en procesos e ingeniería, permite incorporar el contexto único de cada organización en sistemas tecnológicos que amplifican el potencial humano, generan resultados tangibles y mantienen a las empresas a la vanguardia en un entorno en constante cambio. Más información en cognizant.ai o @cognizant.
Información adicional sobre el empleo
La información sobre la compensación es exacta en la fecha de publicación de este anuncio. Cognizant se reserva el derecho de modificar esta información en cualquier momento, de conformidad con la legislación aplicable.
Es posible que se solicite a los solicitantes que asistan a entrevistas de forma presencial o mediante videoconferencia. Asimismo, durante cada entrevista, los candidatos podrán estar obligados a presentar un documento de identidad válido emitido por el estado o por el gobierno.
Cognizant es un empleador que ofrece igualdad de oportunidades. Su solicitud y candidatura no se evaluarán en función de la raza, el color, el sexo, la religión, el credo, la orientación sexual, la identidad de género, el origen nacional, la discapacidad, la información genética, el embarazo, la condición de veterano ni cualquier otra característica protegida por las leyes federales, estatales o locales.
