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Argyllinfotech

Gen AI Architect

Argyllinfotech, Raleigh, North Carolina, United States

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Position: AI Architect Compensation: $120K $125K per annum with no benefits

*Visa Independent Candidates only*

**Local to Charlotte Only**

Onsite Interview and Onsite from Day 1

Job Overview We are seeking a highly skilled

AI Architect

to design and drive our Artificial Intelligence strategy and solutions. The ideal candidate will have deep expertise in Machine Learning (ML), Generative AI (GenAI), and Large Language Model (LLM) frameworks. This role involves architecting end-to-end AI systems, guiding development teams, and ensuring robust, ethical, and scalable AI implementations.

Key Responsibilities

Define and execute the

AI/ML architecture and roadmap , covering both traditional ML and Generative AI use cases.

Design

end-to-end AI solutions

encompassing data ingestion, feature engineering, model training, inference pipelines, and monitoring frameworks.

Lead the

integration of LLMs and RAG (Retrieval-Augmented Generation)

frameworks using tools such as

LangChain ,

LangGraph , or similar.

Collaborate with cross-functional teams to translate

business objectives into AI-driven solutions .

Evaluate and recommend

AI/ML tools, cloud services, and frameworks

best suited for each use case.

Ensure

model governance, security, explainability , and adherence to

ethical AI practices .

Partner with engineering teams to

implement scalable and high-performance AI components .

Work closely with DevOps to establish

CI/CD pipelines for AI , including model versioning, deployment, and A/B testing.

Stay updated on

AI research, trends, and innovations , providing strategic recommendations for adoption.

Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Proven experience in

AI/ML solution architecture

and

cloud-based deployments

(AWS, Azure, or GCP).

Hands-on experience with

LLMs, RAG, vector databases , and

prompt engineering .

Strong programming skills in

Python

and familiarity with ML libraries such as

TensorFlow, PyTorch, or Hugging Face .

Experience designing

scalable microservice-based AI systems .

Excellent communication, collaboration, and problem-solving skills.

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