Associate Forward Deployed Engineer
Listed on 2026-02-28
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IT/Tech
Cloud Computing, IT Support, AI Engineer, Systems Engineer
Eligibility & Location
This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.
New & Recent GraduatesNew & Recent Graduates - This role was designed with you in mind. If you have a strong technical foundation, thrive on a team, and are excited to relocate to Hawaii for a mission‑driven career, we want to hear from you.
Who We AreRaft () is a customer‑obsessed non‑traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting‑edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting‑edge tech stack, and cloud‑native ecosystem.
We build digital solutions that impact the lives of millions of Americans.
We’re seeking a motivated Associate Forward Deployed Engineer to serve as a technical face to our users at Schofield Barracks, Hawaii. This is a customer‑facing position where your communication skills matter just as much as your technical chops. You’ll be an on‑the‑ground technical expert for our customers; troubleshooting system issues, supporting production deployments, and building trusted relationships with the people who depend on our technology every day.
This is an ideal launchpad for a recent graduate who wants to grow fast in a real‑world engineering environment, work closely with senior engineers, and make an immediate impact on mission‑critical systems.
What You’ll Do- Deploy, maintain, and support containerized applications in Kubernetes environments
- Provide technical support for CI/CD pipelines and container orchestration platforms
- Diagnose and resolve technical issues across diverse technology stacks by troubleshooting and debugging production systems at the system level, ensuring maximum uptime and performance
- Collaborate with backend engineering teams to implement solutions and improvements
- Support operational deployments and maintain system reliability in production environments
- Interface directly with customer stakeholders in secure environments making strong interpersonal and communication skills essential
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field (completed within the last year, or graduating by summer 2026)
- Foundational understanding of software engineering principles and practices gained through coursework, internships, capstone projects, or personal projects
- Comfortable using AI tools as a force multiplier, including for debugging, documentation, and rapid prototyping, while maintaining critical evaluation of AI‑generated outputs
- Foundational understanding of machine learning concepts including supervised/unsupervised learning, model training and evaluation, and common algorithms (regression, classification, clustering)
- Exposure to containerization technologies (e.g., Docker, Kubernetes) through coursework, labs, internships, or self‑directed learning
- Familiarity with CI/CD concepts and tools (e.g., Jenkins, Git Lab CI, Git Hub Actions)
- Demonstrated experience working on a team - whether through collegiate sports, internships, academic group projects, hackathons, open‑source contributions, or extracurricular technical teams
- Excellent verbal and written communication skills with a natural ability to interface with both technical and non‑technical stakeholders
- Outgoing, personable demeanor with a genuine interest in customer‑facing work
- Willingness to relocate to Oahu, Hawaii for full‑time onsite work at Schofield Barracks and Hickam AFB
- Experience in software engineering and Dev Ops through coursework, internships, capstone projects, or personal projects
- Coursework or project experience with Linux environments
- Exposure to cloud platforms (AWS, Azure, or GCP) through coursework, personal projects, or certification
- Experience working with common AI/ML…
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