Full-Stack Platform Engineer
New
J
JobgetherFederal technology
This opportunity is based in the United States.Full-TimeSenior
Salary190,000 - 215,000 USD per year
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Job Details
- Experience
- At least 10 years of software or platform engineering experience, including senior technical leadership or solution architecture responsibilities.
- Required Skills
- AWSDockerNode.jsPythonKubernetesReactRESTful APIsDatabricks
Requirements
- Hold a bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical discipline.
- Have at least 10 years of software or platform engineering experience, including senior technical leadership or solution architecture responsibilities.
- Bring hands-on experience with React, Python and/or Node.js, REST APIs, and advanced SQL.
- Have experience designing and supporting cloud-based solutions using AWS.
- Be familiar with Databricks or equivalent data and analytics platforms.
- Have experience implementing CI/CD pipelines and modern DevSecOps practices.
- Have hands-on knowledge of Docker, Kubernetes or Amazon ECS, Terraform, Git, and automated security testing tools.
- Understand application security, IAM/RBAC, OWASP practices, observability, and secure cloud architecture.
- Have experience supporting federal government or other regulated environments.
- Be familiar with FISMA, NIST SP 800-53, FedRAMP, and Authority to Operate processes.
- Be able to lead complex technical initiatives, mentor engineers, and make architectural decisions.
- Have analytical and troubleshooting skills for resolving platform and infrastructure issues.
- Preferred: AWS or other cloud architecture credentials; CISSP or CompTIA Security+; Databricks or data engineering credentials; or CKA, CKS, or comparable certifications.
Responsibilities
- Lead the architecture, design, and development of full-stack applications using React, Node.js/Express, Python frameworks, REST APIs, and advanced SQL.
- Design and maintain cloud data integrations, ETL/ELT pipelines, and data processing solutions using Databricks or equivalent platforms.
- Develop data quality capabilities to support accurate, consistent, and reliable enterprise data.
- Establish secure engineering and DevSecOps practices, including CI/CD pipelines, automated security testing, containerization, infrastructure as code, and code reviews.
- Integrate AI and machine learning capabilities, including LLM APIs, retrieval-augmented generation, and prompt engineering, into enterprise applications.
- Ensure secure handling and processing of sensitive information in AI-enabled applications and data workflows.
- Architect and implement AWS solutions using appropriate identity and access management, networking, secrets management, encryption, logging, and security controls.
- Provide technical leadership and architectural guidance throughout the software development lifecycle, and mentor engineering teams.
- Troubleshoot complex platform and production issues, identify root causes, and implement solutions.
- Communicate technical recommendations, architectural decisions, and risks to stakeholders, and align solutions with federal security requirements.
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