Specialist , FullStack Engineering

Current Employees apply HERE

Current Contingent Workers apply HERE

As a Full-Stack Software Engineer, you will design, develop, and maintain secure, scalable software solutions across the user experience, application, data, and cloud layers. You will leverage modern engineering practices, including cloud-native development, DevOps automation, and AI-assisted software engineering, to deliver high-quality business solutions.

• Develop and maintain complex full-stack applications and software configurations in collaboration with global cross-functional teams
• Develop responsive, accessible user interfaces using modern web technologies, including HTML, CSS, JavaScript/TypeScript, and at least one contemporary frontend framework or library (e.g., React, Angular, Vue, or equivalent).
• Design and implement RESTful APIs and micro-services using technologies such as Node.js/Express or equivalent
• Design test cases and test scripts independently, mapping back to pre-determined criteria, recording and reporting test outcomes
• Ensure quality through automated and manual testing, code reviews, and participation in design and requirements discussions
• Build, deploy, and operate applications on cloud platforms (AWS and/or Azure and/or GCP), following cloud-native best practices
• Use DevOps tools and practices (e.g., Git, CI/CD, infrastructure as code, monitoring/observability) for versioning, deployment, and release automation
• Leverage modern developer productivity tools (e.g., GitHub Copilot or similar AI-assisted development tools) to improve coding efficiency and quality
• Apply secure development practices, including API security, authentication/authorization, and data protection
• Gather requirements and design lifecycle practices and automation for secure, well-engineered systems and microservices
• Follow Digital SDLC practices, ensuring appropriate documentation, compliance, and governance across all development phases (design, build, test, deploy)
• Participate in Agile delivery processes using tools such as Jira for backlog management, sprint planning, status tracking, and cross-team collaboration
• Use AI-assisted development tools (e.g., GitHub Copilot) to accelerate coding, testing, and documentation, while applying sound judgment to review and validate AI-generated output.
• Apply AI capabilities responsibly in software engineering, including evaluating, integrating, or developing AI-enabled features, leveraging LLM-based services and AI-assisted development tools while following security, privacy, and Responsible AI guidelines.
• Collaborate in the design and implementation of intelligent applications, APIs, or workflows that incorporate AI/GenAI capabilities where appropriate to deliver business value.
• Contribute to product planning, execution, and delivery within a matrix organization
• Support performance optimization and scalability improvements across applications

• Bachelor’s degree in Information Technology, Computer Science, or related field
• 3–7 years of hands-on experience working in full-stack development
• Proficiency in at least one major software development stack (TypeScript/Node.js, Java, Python, or .NET) and experience with at least one modern frontend framework/library such as React, Angular, Vue, or equivalent.
• Knowledge of web fundamentals: HTML, CSS, HTTP, REST APIs
• Familiarity with SQL and relational database design (plus practical query optimization)
• Familiarity with cloud platforms (preferably AWS and/or Azure and/or GCP) and cloud-native concepts (e.g., microservices, containerization, managed services)
• Experience with DevOps practices (Git, infrastructure as code, observability, CI/CD)
• Experience working in Agile/Scrum environments with tools such as Jira or equivalent
• Experience working in LangChain or LangGraph or Semantic Kernel. 
• Experience designing, developing, or integrating AI-enabled solutions, including GenAI applications, Retrieval-Augmented Generation (RAG), AI agents, vector databases, AI observability, or responsible AI practices.
• Experience in advanced prompt engineering. 
• Strong problem-solving skills with a product and customer-centric mindset

• Cloud-native, AWS/GCP certified
• Familiarity with secure coding and compliance practices
• Basic understanding of Digital SDLC or regulated development lifecycle practices (e.g., documentation, testing, compliance requirements)
• Foundational awareness of AI/GenAI concepts, including prompt engineering basics, RAG patterns, or usage of AI-assisted tools within the software development lifecycle.
• Familiarity with Responsible AI Practices.