Principal Architect – Agentic AI & LLM Systems

Atlanta, GA - USA

Monthly Salary: Not Disclosed

Posted on: 7 hours ago

Vacancies: 1 Vacancy

Job Summary

Role Overview

We are seeking a senior technical leader to architect scale and lead the development of Agentic AI systems capable of multi-step reasoning and autonomous action. This role will drive application modernization initiatives by embedding advanced Generative AI and LLM workflows into enterprise platforms while shaping the long-term vision for reusable AI capabilities.

Key Responsibilities

Analyze and understand existing legacy systems to design and architect scalable Agentic AI solutions for application modernization.
Define and standardize reference architectures for container-based application hosting vector-based memory systems and resilient data pipelines.
Lead the product and technical vision for reusable AI modules including Retrieval-Augmented Generation (RAG) hybrid ML/LLM systems and standardized evaluation frameworks.
Evaluate and select the LLM technology stack (models orchestration frameworks observability and tooling) based on cost latency performance and scalability.
Establish and standardize advanced prompting strategies including few-shot learning reasoning-based prompting and automated chunking techniques to optimize accuracy and cost efficiency.
Drive engineering productivity by championing AI-assisted development workflows to accelerate development and modernization efforts.
Integrate LLM-powered workflows into existing enterprise systems ensuring interoperability reliability and high-performance outputs.
Partner with security and governance teams to enforce AI safety data privacy compliance and ethical AI standards.
Recruit mentor and lead a high-performing Generative AI engineering team fostering a culture of technical excellence and continuous learning.
Act as a subject matter expert for internal stakeholders and post-implementation engagements translating complex AI concepts into actionable technical and business strategies.

Required Qualifications

10 years of experience in AI/ML engineering with hands-on experience designing and delivering production-grade systems.
At least 1 year of experience working with Agentic AI systems and Large Language Models.
Strong hands-on development experience using AI-assisted coding tools for rapid prototyping and implementation.
Expertise in at least one major cloud platform (AWS Azure or GCP).
Deep proficiency in agentic workflow frameworks and memory architectures including graph-based orchestration and vector storage.
Experience working with reasoning instruction-tuned safety and embedding models.
Extensive experience with LLM evaluation testing and benchmarking frameworks including prompt testing and agent evaluation methodologies.

Preferred Attributes

Strong architectural judgment with the ability to balance innovation scalability security and cost.
Excellent communication skills with the ability to influence technical and non-technical stakeholders.
Proven leadership experience guiding senior engineers and cross-functional teams.

Role Overview We are seeking a senior technical leader to architect scale and lead the development of Agentic AI systems capable of multi-step reasoning and autonomous action. This role will drive application modernization initiatives by embedding advanced Generative AI and LLM workflows into enterp...

Role Overview

Key Responsibilities

Analyze and understand existing legacy systems to design and architect scalable Agentic AI solutions for application modernization.
Define and standardize reference architectures for container-based application hosting vector-based memory systems and resilient data pipelines.
Lead the product and technical vision for reusable AI modules including Retrieval-Augmented Generation (RAG) hybrid ML/LLM systems and standardized evaluation frameworks.
Evaluate and select the LLM technology stack (models orchestration frameworks observability and tooling) based on cost latency performance and scalability.
Establish and standardize advanced prompting strategies including few-shot learning reasoning-based prompting and automated chunking techniques to optimize accuracy and cost efficiency.
Drive engineering productivity by championing AI-assisted development workflows to accelerate development and modernization efforts.
Integrate LLM-powered workflows into existing enterprise systems ensuring interoperability reliability and high-performance outputs.
Partner with security and governance teams to enforce AI safety data privacy compliance and ethical AI standards.
Recruit mentor and lead a high-performing Generative AI engineering team fostering a culture of technical excellence and continuous learning.
Act as a subject matter expert for internal stakeholders and post-implementation engagements translating complex AI concepts into actionable technical and business strategies.

Required Qualifications

10 years of experience in AI/ML engineering with hands-on experience designing and delivering production-grade systems.
At least 1 year of experience working with Agentic AI systems and Large Language Models.
Strong hands-on development experience using AI-assisted coding tools for rapid prototyping and implementation.
Expertise in at least one major cloud platform (AWS Azure or GCP).
Deep proficiency in agentic workflow frameworks and memory architectures including graph-based orchestration and vector storage.
Experience working with reasoning instruction-tuned safety and embedding models.
Extensive experience with LLM evaluation testing and benchmarking frameworks including prompt testing and agent evaluation methodologies.

Preferred Attributes

Strong architectural judgment with the ability to balance innovation scalability security and cost.
Excellent communication skills with the ability to influence technical and non-technical stakeholders.
Proven leadership experience guiding senior engineers and cross-functional teams.