Objectives
The objective of this engagement is to provide Full Stack Development expertise to design, develop, implement, and support enterprise AI-enabled applications that improve business productivity, operational efficiency, and decision-making across client Distribution Systems & Components.
Specific objectives include:
- Design and develop secure, scalable, and maintainable enterprise web applications supporting AI and advanced analytics initiatives.
- Build intuitive user interfaces that enable business users to interact with AI-generated recommendations, predictive insights, and intelligent workflows.
- Develop backend services, APIs, and application logic that integrate AI/ML models with enterprise systems and business processes.
- Enable Human-in-the-Loop (HITL) workflows allowing business users to review, validate, modify, and approve AI-generated outputs before operational execution.
- Develop reusable application components and frameworks that can be leveraged across multiple AI initiatives within the BDS&C portfolio.
- Modernize existing analytics applications and dashboards through improved user experiences, responsive interfaces, and enhanced visualization capabilities.
- Integrate enterprise applications with cloud platforms, databases, APIs, authentication services, workflow engines, and AI services.
- Improve operational efficiency through workflow automation, intelligent process orchestration, and digital transformation initiatives.
- Support deployment, monitoring, optimization, maintenance, and continuous enhancement of enterprise AI applications while adhering to client software engineering, cybersecurity, and governance standards.
- Develop reusable application frameworks and components that can be leveraged across multiple enterprise AI initiatives.
- Collaborate with cross-functional teams to ensure applications align with business objectives, enterprise architecture, and client software engineering standards.
- Support continuous improvement by incorporating user feedback, operational metrics, and evolving business requirements into future application enhancements.
Representative AI & Business Solution Areas:
The Full Stack Developer will support a broad portfolio of AI and Advanced Analytics initiatives. Representative examples include, but are not limited to, the following:
- Part Build Record (PBR) AI Application: Design and develop enterprise web applications that enable users to review, validate, edit, and approve AI-generated recommendations for supplier part onboarding. The application will support intelligent document processing, compliance validation, auditability, workflow approvals, and seamless interaction between AI models and business users.
- Conversational AI & Enterprise Knowledge Assistant: Develop intuitive conversational interfaces enabling employees to search, retrieve, and interact with enterprise knowledge, technical documentation, operational procedures, manuals, structured data, and AI-generated insights using natural language interactions.
- Business Intelligence & Analytics Modernization: Develop modern enterprise dashboards and analytical applications that enhance visualization, reporting, and executive decision support by integrating AI-generated insights with operational and business performance metrics.
- Workflow Automation Applications: Develop enterprise workflow applications that streamline business processes by integrating AI recommendations with approval workflows, notifications, task management, and business process automation.
- Agentic AI Solutions: Support development of next-generation AI applications that enable autonomous decision support, intelligent orchestration, multi-agent collaboration, and AI-assisted operational workflows while maintaining appropriate business oversight and governance.
- Enterprise AI Platform Components: Develop reusable UI components, application frameworks, integration services, and shared functionality that accelerate development of future AI products across the BDS&C AI & Analytics portfolio.
- Predictive Analytics Applications: Develop user-facing enterprise applications that present AI-generated forecasts, predictive insights, and operational recommendations through interactive dashboards and intuitive workflows, enabling business users to make informed decisions across supply chain and operational processes.
Resourcing
- Full Stack Development expertise is required to support the successful design, implementation, deployment, integration, and sustainment of enterprise AI applications across client Distribution Systems & Components.
- The resource will possess strong experience in enterprise software development, modern web application technologies, cloud-native application development, API integration, AI application enablement, and enterprise system integration.
- The individual will collaborate with cross-functional technical and business teams to develop scalable, secure, and production-ready applications that enable successful adoption of AI capabilities throughout the organization.
- The Full Stack Developer will support the entire software development lifecycle including requirements analysis, solution design, application development, integration, testing, deployment, documentation, production support, and knowledge transfer while ensuring compliance with client technical standards, security requirements, accessibility guidelines, and software engineering best practices.
The Full Stack Developer shall provide technical expertise to design, develop, implement, integrate, deploy, and support enterprise web applications that enable Artificial Intelligence (AI), Machine Learning (ML), Generative AI (GenAI), Agentic AI, and Advanced Analytics capabilities across client Distribution Systems & Components (BDS&C). Services include, but are not limited to, the following:
- Requirements Analysis & Solution Design: Collaborate with Product Managers, Business Stakeholders, Solution Architects, Data Scientists, Data Engineers, and Subject Matter Experts (SMEs) to gather functional and technical requirements, define solution architecture, and translate business needs into scalable application designs.
- Front-End Application Development: Design and develop responsive, intuitive, and accessible user interfaces using modern web technologies to support AI-enabled business applications while ensuring an optimal user experience across desktop and mobile platforms.
- Back-End Application Development: Develop secure backend services, business logic, APIs, middleware, and integration components that enable seamless communication between enterprise applications, AI models, and business systems.
- API Development & Integration: Design, develop, consume, and maintain RESTful APIs and microservices that integrate enterprise applications with AI models, databases, authentication services, cloud platforms, workflow engines, and other internal or external systems.
- AI Application Integration: Develop application components that enable business users to interact with AI-generated recommendations, predictive analytics, intelligent document processing, conversational AI, and other AI-powered capabilities while supporting Human-in-the-Loop (HITL) review and validation workflows.
- Workflow Automation: Develop business workflow applications supporting approvals, task routing, notifications, business rule execution, audit tracking, and process automation that improve operational efficiency and reduce manual effort.
- Dashboard & Visualization Development: Design and develop interactive dashboards, reporting interfaces, visual analytics, and executive-level reporting capabilities that improve business visibility and support data-driven decision making.
- Enterprise System Integration: Integrate applications with enterprise databases, cloud platforms, authentication services, ERP systems, analytics platforms, document repositories, and other enterprise applications while ensuring data integrity and security.
- Security & Compliance: Implement secure coding practices and application security controls while ensuring compliance with client cybersecurity policies, enterprise architecture standards, data privacy requirements, and secure authentication mechanisms.
- Testing & Quality Assurance: Perform unit testing, system testing, integration testing, regression testing, defect resolution, and application validation to ensure software quality, reliability, and production readiness.
- Deployment & Release Management: Support application deployment activities across development, testing, staging, and production environments using established release management processes while minimizing operational disruptions.
- Performance Optimization: Continuously monitor and optimize application performance, scalability, responsiveness, reliability, and resource utilization to ensure enterprise-grade user experiences.
- Application Architecture: Design scalable, modular, and reusable application architectures aligned with client enterprise architecture principles while supporting future enhancements and AI capabilities.
- Code Reviews & Development Standards: Participate in peer code reviews, establish development best practices, maintain coding standards, and ensure applications are secure, maintainable, and consistent across the AI application portfolio.
- Documentation: Develop and maintain technical documentation including application architecture, API documentation, deployment procedures, configuration guides, technical specifications, user manuals, and operational support documentation.
- Agile Delivery Support: Participate in Agile ceremonies including sprint planning, backlog refinement, estimation sessions, daily stand-ups, sprint reviews, retrospectives, and release planning activities while collaborating with cross-functional delivery teams.
- Knowledge Transfer: Provide knowledge transfer sessions, technical walkthroughs, implementation guidance, and operational support documentation to client technical teams to ensure successful transition and long-term maintainability.
- Production Support & Continuous Improvement: Support post-deployment stabilization activities, troubleshoot application issues, implement enhancements, resolve defects, monitor application health, and recommend improvements that enhance business value and user adoption.
Technical Expertise
The Full Stack Developer shall possess demonstrated experience in the following areas:
- Enterprise web application architecture and software engineering principles.
- Modern JavaScript frameworks such as React, Angular, or Vue.js.
- HTML5, CSS3, JavaScript, and TypeScript.
- Backend development using technologies such as Node.js, Java, .NET, or similar enterprise platforms.
- RESTful API development and microservices architecture.
- Integration with AI/ML services, Generative AI applications, and Large Language Models (LLMs).
- Enterprise authentication mechanisms including OAuth, SSO, JWT, and role-based access control.
- Cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform (GCP).
- SQL and NoSQL database technologies.
- CI/CD pipelines, Git version control, and DevOps best practices.
- Containerization technologies such as Docker and Kubernetes.
- Secure application development and cybersecurity best practices.
- Application performance tuning and scalability optimization.
- Responsive UI/UX design and accessibility standards.
- Agile software development methodologies and collaborative delivery models.
- Strong analytical, troubleshooting, communication, and problem-solving skills.
- Experience integrating Large Language Models (LLMs), Generative AI services, and AI agents into enterprise applications.
- Familiarity with enterprise application architecture, design patterns, and reusable component development.
- Experience implementing secure software development lifecycle (SSDLC) practices.
#LI-Onsite
