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# AI FS DEVELOPER

- **Company:** Arc Full-time
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $60,000.0 - $105,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Application Frameworks, Microsoft Azure, Cloud Computing, Cyber Security, Middleware, Software Engineering, Delivery Pipeline, Large Language Models, IT Architecture, Information Technology, Api Gateway
- **Published:** August 9, 2026
- **Apply:** https://arc.dev/signup?userType=developer&publicRandomKey=pamf0p0nky&to=https%3A%2F%2Farc.dev%2Fdashboard%2Fd%2Fverified-jobs%2Fpamf0p0nky%2Fapplication

## About the Role

* BA/BS in Information Security, Computer Science, MIS, or related field (or equivalent experience).
 * 3-6+ years of experience in Application Development, AI or other related fields.
 * Experience reviewing application architectures, APIs, or cloud-based solutions.
 * Experience working with AI/LLMs and agent-based systems.
 * Experience with AI based developer environments and AI focused delivery pipelines.
 * Strong understanding of data protection, access control, and secure design principles.
 * Experience working cross-functionally with engineering and business teams.
 * Strong communication skills with ability to translate risks into actionable guidance., * Experience with AI/LLM platforms (e.g., Azure OpenAI, Gemini).
 * Familiarity with API gateways or middleware architectures.
 * Experience contributing to application frameworks, policies, or standards.
 * Understanding of emerging AI technologies with history building with bleeding edge tools.

## Description

Full Stack Application Developer - AI Focused Engineering will play a critical role in modern, scalable applications utilizing AI principles in an Enterprise environment. This role sits at the intersection of Development, Architecture, and AI, serving as both an empowered contributor and a strategic enabler of AI experimentation., * Assessing AI architectures, including LLM Gateways, MCP Gateways, APIs, and integrations for potential usage and value.

 * Drive AI security governance adoption and define technical guardrails aligned with enterprise policies.
 * Deploy and operationalize AI tooling implementations in partnership with Security and Application teams, specifically targeting developer and pipeline environments.
 * Enable safe AI experimentation by guiding teams on secure design patterns and approved tools.
 * Perform predictability, performance, and scalability assessments for AI use cases.
 * Collaborate with Legal, Privacy, Procurement, and Architecture on AI risk and compliance.
 * Support AI architecture decision-making and contribute to enterprise standards.
 * Monitor evolving AI threats for architecture changes in applications.
 * Document risk decisions and governance outcomes for auditability.
 * Support reporting on AI adoption, performance, and quality metrics.


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