Sr. AI Architect

Accord Technologies Inc; Charlotte (NC); Hybrid; USD 60,000 - 65,000; Full time

Job summary

A technology solutions firm in Charlotte, NC seeks a Sr. AI Architect to drive AI/ML architecture and design AI solutions. This hybrid position requires expertise in generative AI and 10+ years of experience. Responsibilities include leading LLM integration, ensuring model governance, and guiding engineering teams in AI implementations. The role offers a salary range of $60,000 – $65,000 annually.

Qualifications

• Demonstrable experience in AI/ML architecture.
• Proven track record with ML and Generative AI projects.
• Expertise in handling Large Language Models.

Responsibilities

• Define and drive the AI/ML architecture and roadmap.
• Design end-to-end AI solutions including data ingestion.
• Lead the integration of LLMs and RAG frameworks.

Skills

AI/ML architecture

ML and Generative AI (GenAI) use cases

Large Language Models (LLMs)

Retrieval-Augmented Generation (RAG)

LangChain

LangGraph

CI/CD for AI pipelines

10+ years of experience

Job description

Sr. AI Architect

Location: Charlotte, NC
Hybrid: 3 days a week from office
Duration: Long term
Position type: W2 contract

Pay Range

Base pay range: $60,000 – $65,000 per year

Mandatory Skills

• AI/ML architecture
• ML and Generative AI (GenAI) use cases
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• LangChain, LangGraph
• CI/CD for AI pipelines
• 10+ years of experience

Responsibilities

• Define and drive the AI/ML architecture and roadmap, including traditional ML and GenAI use cases.
• Design end-to-end AI solutions including data ingestion, feature engineering, model training, inference pipelines, and monitoring frameworks.
• Lead the integration of LLMs and RAG frameworks using tools such as LangChain, LangGraph, or similar.
• Collaborate with stakeholders to translate business requirements into AI-driven technical solutions.
• Evaluate and select appropriate AI/ML tools, cloud services, frameworks, and libraries for specific use cases.
• Ensure model governance, security, explainability, and compliance with ethical AI practices and regulatory requirements.
• Guide engineering teams in the implementation of AI components, ensuring scalability, reliability, and performance.
• Work with DevOps teams to enable CI/CD for AI pipelines, including model versioning and A/B testing.
• Stay current with industry trends, research, and advancements in AI and recommend best practices for adoption.

Seniority Level

Mid‑Senior level