Top 123 Red teaming retrieval augmented generation Jobs

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AI Engineer

AAIT Health LLC
Little Rock, AR

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Job Details

Full-time

Qualifications

AI models
Systems integration
Software engineering
Engineering development testing
Improving system uptime or availability
Data retrieval time improvement
Generative models
AI platforms (beyond public GPTs)
Collaboration with product development teams
Machine intelligence
Model deployment
Developing large-scale AI models
Developing and maintaining backend systems
Back-end integration
API integration for front-end development
Model evaluation
Generative AI
Debugging
Cross-functional communication

Full Job Description

Description:

About Us

AAIT Health (Advanced Artificial Intelligence Technology Health) is building a modern, HIPAA-compliant Electronic Medical Records (EMR) platform. We’re focused on turning today’s best AI and LLM capabilities into reliable, secure, production-grade workflows embedded directly into the EMR experience, so clinicians and staff can work smarter, faster, and with less administrative burden.

What You’ll Do

Build agentic AI systems that can execute multi-step workflows (e.g., chart review ? summarize ? recommend next actions ? draft documentation ? route tasks) with appropriate human oversight.
Design and implement tool-using LLM workflows (function calling / tools, retrieval, structured outputs, planner–executor patterns, and guardrails).
Integrate AI capabilities into our EMR via backend services and APIs (e.g., .NET Core services, MySQL, and modern frontend clients).
Implement retrieval-augmented generation (RAG) and clinical knowledge workflows that query patient context, incorporate medical reference content, and cite sources with traceability.
Engineer safety, privacy, and compliance into AI workflows, including PHI-safe processing, audit logs, role-based access, minimum-necessary data, prompt/data redaction, and secure storage.
Evaluate and improve quality using automated and human-in-the-loop evaluation (e.g., grounding, hallucination rates, task success, latency, and cost).
Deploy and operate AI services in production, including monitoring, rate limiting, fallbacks, caching, incident response, and model/provider switching.
Collaborate cross-functionally with product, clinical SMEs, security/compliance, and engineering to ship AI-powered features that users trust.

Role Details

Full-time position with presence in the office required.
Core schedule: Monday–Thursday 8:00 a.m. to 5:00 p.m. and Friday 8:00 a.m. to 12:00 p.m., with occasional work outside regular business hours as needed.
Travel may be required.
The position operates in a professional office environment and involves significant time writing, typing, speaking, listening, standing, sitting, walking, and reaching.
Operation of standard office equipment, non-CDL motor vehicles, mobile phones, and related technology is expected.

Requirements:

You Might Be a Fit If

You have strong software engineering fundamentals and production experience (APIs, testing, debugging, performance).
You have hands-on experience building with LLMs (OpenAI/Anthropic/others), including tool/function calling, structured outputs, and retrieval-augmented generation (RAG).
You’ve integrated AI into real products (not just notebooks or demos) and understand the tradeoffs of latency, cost, and quality.
You can design for reliability with deterministic interfaces, schema validation, retries, fallbacks, and evaluation.
You are comfortable working across backend and data, and optionally some frontend integration.
You communicate clearly, enjoy collaborating with cross-functional partners, and can explain complex AI behavior to non-technical stakeholders.
You are comfortable operating in a startup-like environment, prioritizing impact and iterating quickly while maintaining quality.

Bonus Points

Experience in healthcare, EMR, or clinical workflows; familiarity with standards such as HL7/FHIR.
Experience with .NET Core, MySQL, and cloud deployment (Azure is a plus).
Familiarity with security and compliance practices such as HIPAA and SOC2-style controls, including RBAC and audit logging.
Experience building evaluation pipelines (golden datasets, offline eval, red-teaming, prompt regression tests).
Experience with vector databases/search or building retrieval layers over relational and document stores.
Knowledge of PHI de-identification, redaction, and safe data handling.

Tech Stack

Frontend: React + Vite + TypeScript
Backend: .NET Core services
Database: MySQL
Cloud: Azure, AWS
AI: LLM APIs, retrieval/vector search, observability & evaluation tooling

Quick Apply

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