Senior Full Stack Engineer

Vizient•Irving, TX

3d•$102,400 - $179,000

About The Position

Design, develop, and support modern cloud-native applications that enable enterprise analytics, data-driven workflows, AI-enabled capabilities, and operational decision-making. Deliver end-to-end solutions across the user interface, application, integration, and data layers, including modern React experiences, scalable Node.js services, secure APIs, enterprise integrations, and reliable data-access solutions using relational and analytical data platforms. Work closely with Product Managers, Architects, AI Engineers, Data Engineers, Quality Engineers, and Cloud and DevOps Engineers to deliver secure, scalable, maintainable, and user-centered business solutions. The role calls for strong front-end and back-end engineering experience, along with expertise in cloud-native delivery, relational databases, automated testing, and production operations.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, a related field, or equivalent practical experience.
Five or more years of software engineering experience building and supporting enterprise applications.
Strong hands-on experience with React, TypeScript, JavaScript, and modern front-end development practices.
Strong hands-on experience with Node.js, TypeScript, API design, and backend service development.
Experience designing and implementing RESTful APIs, microservices, and enterprise integrations.
Strong SQL and relational database skills, including data modeling, schema design, indexing, query optimization, and transaction management.
Experience with relational databases such as PostgreSQL, SQL Server, MySQL, or comparable platforms.
Experience consuming governed data from analytical platforms such as Databricks, Snowflake, or comparable technologies.
Experience with Git, CI/CD pipelines, automated testing, code reviews, and modern software delivery practices.
Knowledge of cloud-native application architecture, containerized deployment, authentication, authorization, secure coding, and production operations.
Experience implementing automated unit, integration, API contract, component, and end-to-end testing.
Experience implementing application observability, including logging, monitoring, tracing, health checks, and operational metrics.
Strong analytical, problem-solving, communication, and cross-functional collaboration skills.

Nice To Haves

Experience with Docker, Kubernetes, event-driven architectures, and enterprise messaging platforms.
Experience building analytics, reporting, workflow, dashboarding, or decision-support applications.
Experience integrating applications with AI-enabled or large language model services and agentic workflows.
Experience with Databricks, Delta Lake, Snowflake, or governed enterprise data products.
Experience with front-end state management, component testing, API contract testing, and end-to-end test automation.
Experience using AI-assisted development tools for coding, testing, documentation, technical research, and troubleshooting.
Experience working in healthcare, supply chain, analytics, or another regulated and data-intensive environment.
Relevant cloud, software development, or technology certifications.

Responsibilities

Design, develop, test, deploy, and maintain enterprise web applications using React, TypeScript, Node.js, and related technologies.
Deliver application functionality across presentation, application, integration, and data layers, translating requirements into secure, maintainable, production-ready solutions.
Build responsive, accessible user experiences and reusable UI components, shared libraries, and engineering patterns; optimize applications for performance, testability, and maintainability.
Collaborate with Product and user-experience partners to translate workflows and requirements into effective enterprise application experiences.
Implement secure authentication, authorization, and session-management patterns in user-facing applications.
Design and develop RESTful APIs, backend services, and microservices using Node.js and TypeScript; build scalable services for workflows, analytics, AI-enabled capabilities, and enterprise integrations.
Implement secure service-to-service communication, input validation, error handling, resiliency, and operational safeguards.
Integrate applications with internal platforms, APIs, event streams, analytical data platforms, and external enterprise systems using appropriate synchronous, asynchronous, and event-driven patterns.
Design relational data models and schemas; develop and optimize SQL queries, views, stored procedures, and persistence logic.
Apply indexing, query optimization, transaction management, and performance-tuning practices, and build services that reliably consume and expose governed operational and analytical data.
Collaborate with Data Engineers on trusted enterprise data products and analytical platforms, contributing to data quality, security, lineage, migration, and production support.
Develop applications for cloud-native deployment and containerized runtime environments; support Docker and Kubernetes deployment patterns and CI/CD automation.
Implement structured logging, distributed tracing, application monitoring, health checks, alerting, and operational metrics.
Write and maintain automated unit, integration, contract, component, and end-to-end tests.
Support production troubleshooting, incident investigation, root cause analysis, remediation, and continuous improvement.
Apply secure coding, API security, dependency-management, and software supply-chain practices; work with Architects to implement approved solution, security, data, and integration patterns.
Collaborate with AI Engineers and Data Engineers to deliver intelligent, data-driven product capabilities.
Participate in product discovery, estimation, technical design, code reviews, testing, release planning, and operational-readiness activities.
Mentor engineers and contribute to shared development standards, technical documentation, reusable components, and engineering accelerators.
Use AI-assisted engineering tools responsibly to improve research, development, testing, documentation, code quality, and troubleshooting.