Full-Stack Platform Engineer

About the role

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Full-Stack Platform Engineer based in the United States.

We are seeking an experienced Full-Stack Platform Engineer to provide technical leadership and hands-on engineering for a secure enterprise data analytics platform supporting federal operations. In this role, you will architect and develop scalable web applications, APIs, cloud solutions, and complex data integrations. You will leverage modern technologies such as React, Node.js, Python, AWS, and advanced data platforms to deliver reliable and high-performance solutions. You will also drive secure software development practices, DevSecOps automation, and the integration of AI and machine learning capabilities. Working within a mission-driven environment, you will collaborate with multidisciplinary teams, mentor engineers, and guide critical technical decisions. This fully remote opportunity offers the chance to contribute to impactful federal technology initiatives while working on modern, security-focused engineering solutions.

Accountabilities As a Full-Stack Platform Engineer, you will lead the architecture, development, and continuous improvement of enterprise platforms while ensuring security, scalability, and operational reliability. Your responsibilities will include:

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Lead the architecture, design, and development of full-stack applications using React, Node.js/Express, Python frameworks such as Flask and FastAPI, REST APIs, and advanced SQL.

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Design, implement, and maintain cloud-based data integrations, ETL/ELT pipelines, and data processing solutions using Databricks or equivalent analytics platforms.

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Develop and enhance data quality capabilities to ensure the accuracy, consistency, and reliability of enterprise data.

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Establish and promote secure engineering and DevSecOps practices, including CI/CD pipelines, automated security testing, containerization, infrastructure as code, and code reviews.

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Integrate AI and machine learning capabilities into enterprise applications, including LLM APIs, retrieval-augmented generation (RAG), and advanced prompt engineering techniques.

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Ensure the secure handling and processing of sensitive information within AI-enabled applications and data workflows.

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Architect and implement solutions within AWS, applying appropriate identity and access management, networking, secrets management, encryption, logging, and security controls.

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Provide technical leadership and architectural guidance throughout the software development lifecycle.

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Mentor and support engineering teams, promoting technical excellence, knowledge sharing, and engineering best practices.

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Troubleshoot complex platform and production issues, identify root causes, and implement effective solutions.