Full-Stack Engineer – AI-Native Solutions

Guidehouse•Tysons Corner, VA

About The Position

Build, test, deploy, and maintain secure, scalable full-stack enterprise software within Guidehouse’s Chief Transformation Officer (CXO) organization, supporting AI Transformation, Solution Studio, and other strategic CXO initiatives. This hands-on engineering role uses AI coding assistants and agents throughout software development, with human review and verification, and incorporates generative AI capabilities where they add value. Collaborating with Technical Product Managers and architects, the engineer delivers reliable, maintainable applications that meet business and technical requirements. Work may include production-scale solutions, prototypes, or MVPs, depending on the assignment. Solutions span front-end experiences, backend services and APIs, data persistence, enterprise integrations, and authentication and authorization. The role also involves deploying and operating cloud-native solutions, applying enterprise security, privacy, and responsible AI controls, and monitoring and troubleshooting deployed systems. The engineer maintains technical documentation and support runbooks and coordinates production readiness and handoff with IT and business owners. Travel required is up to 10%. The position requires the ability to obtain Public Trust clearance.

Requirements

Bachelor’s degree, or four additional years of professional experience in lieu of a degree.
At least four years of software engineering experience, including independently delivering production full-stack applications and deploying or operating cloud-native services.
Hands-on proficiency with JavaScript/TypeScript and a modern front-end framework, plus Python or another backend language.
Experience with APIs, databases, authentication, and enterprise integrations.
Practical experience using AI coding assistants or agents, including giving clear instructions, critically reviewing generated code, and validating behavior through tests and debugging.
At least one year of hands-on experience integrating generative AI or agent capabilities into applications, including understanding their limitations and evaluation needs.
Experience with a major cloud platform, Git, automated testing, CI/CD, containers, and infrastructure as code.
Ability to troubleshoot using logs, metrics, and traces.
Strong written and verbal communication skills, including explaining technical concepts and tradeoffs to technical and nontechnical audiences and engaging credibly in stakeholder and client discussions.
Ability to obtain Public Trust clearance.

Nice To Haves

Experience in client-facing solution engineering or consulting, or in enterprise transformation within a matrixed organization.
Familiarity with workflows and regulatory requirements in Guidehouse industries: Healthcare; Financial Services; Communities, Energy & Infrastructure; and Defense & Security.
Experience delivering production-scale solutions with demanding performance or reliability requirements, or developing reusable components and AI-assisted delivery practices.
Relevant cloud, DevOps, or AI certifications.
Master’s degree in a relevant technical or business discipline.

Responsibilities

Build, test, deploy, and maintain secure, scalable full-stack enterprise applications, including production-scale solutions, prototypes, and MVPs as required.
Develop end-to-end applications with front-end experiences, backend services and APIs, data persistence, enterprise integrations, and authentication and authorization.
Use AI coding assistants and agents for implementation, refactoring, testing, debugging, and documentation; review and validate generated work for correctness, security, and maintainability.
Engineer for performance, reliability, scalability, and maintainability, validating behavior through automated tests, code reviews, and representative workloads.
Integrate generative AI, retrieval-augmented generation (RAG), agents, and tool calling where appropriate; assess solution quality, latency, cost, and security before scaling.
Collaborate with Technical Product Managers and architects to clarify requirements, estimate engineering work, and communicate technical tradeoffs, dependencies, and delivery risks.
Deploy and operate cloud-native solutions using automated testing, CI/CD, infrastructure as code, and observability; implement enterprise security, privacy, and responsible AI controls.
Monitor and troubleshoot deployed solutions using relevant diagnostic information.
Maintain technical documentation and support runbooks, and coordinate production readiness and handoff with IT and business owners.
Communicate technical concepts and tradeoffs, demonstrate working solutions, ask clarifying questions, report progress and risks, and participate professionally in stakeholder and client discussions.