About the job
AT&T is ushering in a new era of intelligent automation and secure AI innovation. We are seeking a visionary Principal AI Architect to lead the design, development, and deployment of advanced AI systems that integrate large language models (LLMs), prompt engineering, full-stack development, and AI cybersecurity. This role is ideal for a seasoned technologist with deep expertise in Python, AI agent orchestration, and secure enterprise-grade deployments.
Responsibilities
Architect and implement intelligent automation workflows using LLMs, prompt engineering, and dynamic context management.
Design and optimize prompts for precision and contextual relevance across diverse use cases.
Build and orchestrate multi-agent systems using frameworks like LangGraph.
Integrate LLMs into scalable Python applications using APIs and custom pipelines.
Develop and maintain robust backend services and optional front-end interfaces for end-to-end AI applications.
Lead the development of scalable web applications using Python (FastAPI, Flask, Django) and React.js.
Architect RESTful APIs and integrate third-party services.
Drive best practices in coding, testing, and application architecture.
Mentor junior developers and lead code reviews to ensure technical excellence.
Design and implement security protocols to protect AI systems from emerging cyber threats.
Conduct adversarial testing, vulnerability assessments, and compliance audits.
Develop secure coding standards and guide teams on responsible AI deployment.
Research and apply industry standards (e.g., NIST AI-RMF, ISO42001, OWASP Top 10 for LLMs) to safeguard AI systems.
Qualifications
Minimum
Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, Cybersecurity, or related field preferred.
7+ years of professional experience in full-stack development and AI engineering.
Proven expertise in Python development and modern front-end frameworks (React.js, TypeScript).
Deep experience with LLMs (OpenAI, Anthropic, open-source), prompt engineering, and context management.
Hands-on experience with RAG pipelines, vector search, and multi-agent orchestration.
Strong understanding of cloud infrastructure (AWS, Azure, GCP), containerization (Docker), and CI/CD practices.
Demonstrated experience in AI security, including adversarial testing and secure deployment.
Excellent problem-solving, communication, and leadership skills.
Preferred
No preferred qualifications listed.