Forward Deployed Full Stack Engineer (Active Secret Clearance)

TribalScale

About The Position

TribalScale is seeking a Forward Deployed Full Stack Engineer with an active US Secret clearance to embed with a US government-facing client. The engineer will work directly with end users, product owners, and client technical and security teams to understand workflows, identify needs, and build and deploy software into secure environments. The role combines full-stack development, client engagement, deployment troubleshooting, and explaining technical tradeoffs to non-technical stakeholders. The engineer will own features from initial conversations through production deployment, often working in on-premises, government-cloud, or restricted-network environments. They will turn ambiguous needs into working software through rapid prototyping and iteration, integrate AI features and agentic workflows where appropriate within security and data-handling constraints, and collaborate with client ISSO and compliance teams on authorization requirements. They will also connect field insights to TribalScale’s broader engineering and product teams and help create reusable approaches for future engagements. Success involves building trusted client and TribalScale relationships, understanding the client’s operating environment, and delivering useful software. Over time, the engineer will develop technical plans from loosely defined needs, deliver reliable AI-enabled products, establish evaluation and observability practices, improve agent systems and safeguards, help clients operate AI responsibly, and guide promising ideas into production.

Requirements

Active US Secret clearance or higher, with the ability to maintain it.
US citizenship; the company cannot sponsor a new clearance for this role.
At least 5 years of professional full-stack development experience shipping production software used by real users.
Strong TypeScript front-end skills and experience with a modern framework; React is preferred.
Strong back-end skills in at least one of Python, Node.js, Java, or Go, plus REST and/or GraphQL API design experience.
Relational database experience, such as PostgreSQL, including data modeling and query performance.
Hands-on experience with containers and CI/CD; Docker is required.
Cloud experience on AWS, Azure, or GCP.
Experience working directly with end users or customer stakeholders and explaining technical tradeoffs in plain language.
Regular use of AI coding tools in day-to-day development and an understanding of their strengths and limitations.
Ability to make progress and sound decisions in ambiguous situations.

Nice To Haves

Kubernetes or OpenShift experience.
Experience with government cloud regions such as AWS GovCloud or Azure Government.
Prior forward-deployed, field engineering, or embedded consulting experience.
Experience deploying into air-gapped or disconnected environments.
Familiarity with NIST 800-53, RMF/ATO processes, DISA STIGs, or FedRAMP.
A DoD 8140/8570-aligned certification, such as CompTIA Security+.
Experience building with LLMs, including RAG, agent frameworks, evaluation, or running open-weight models on approved infrastructure.
Active TS or TS/SCI clearance.

Responsibilities

Work on site and remotely with end users, product owners, and client technical and security teams to understand their workflows and needs.
Build and ship production features across the front end, back end, data layer, and infrastructure, owning features from initial discussion through deployment.
Deploy software into on-premises, government-cloud, and restricted-network environments, including constrained environments with limited tooling or internet access.
Prototype quickly, present working software to users, and iterate on ambiguous needs without waiting for complete specifications.
Build LLM-powered features and agentic workflows that comply with client security and data-handling constraints, including use of self-hosted or approved models.
Write code and documentation suitable for security review and work with client ISSO and compliance teams on authorization requirements.
Share field insights with TribalScale’s engineering and product teams and bring in specialists as engagement needs require.
Turn loosely defined client needs into executable technical plans and deliver reliable AI-enabled products.
Establish evaluation and observability practices to measure quality and identify regressions.
Improve agent behavior by refining harnesses, loops, tools, graphs, context, and safeguards.
Help client teams understand AI system capabilities, failure modes, and responsible operating practices.
Create reusable technical patterns for future TribalScale engagements.