Role overview

Qualifications

10+ years' experience in enterprise-wide AI programs or platform buildouts
Bachelor's degree in Computer Science, Engineering, or a related field
5+ years of experience in application development, engineering, or solution delivery roles
Strong hands-on experience with machine learning frameworks and LLM platforms

Responsibilities

Provide architectural oversight across AI/ML projects to ensure consistency, performance, and maintainability
Evaluate and select AI technologies, frameworks, cloud services, vector databases, LLM orchestration frameworks, and tooling
Support development teams on model selection, training pipelines, prompt engineering, fine tuning, RAG (Retrieval-Augmented Generation), and evaluation methodologies
Mentor engineers, analysts, and product teams on AI best practices

Key facts

Remote from: Massachusetts (USA)
Full time
Expert & Leadership (>10 years)
English

Hard skills

Solution Architecture Machine Learning Python (Programming Language) Data Governance Information Privacy Personal Security Model Risk Management Mload AI/ML Inference Data Science Azure Machine Learning OpenAI Gym Kubernetes Embedding Vector Data Evaluation Strategy

Other skills

Problem Solving
Mentorship

About the company

Global Channel Management, Inc.

Human Resources, Staffing & Recruiting

Global Channel Management is a technology company that specializes in various types of recruiting and staff augmentation. Our account managers and recruiters have over a decade of experience in various verticals. GCM understands the challenges companies face when it comes to the skills and experience needed to fill the void of the day to day function. Organizations need to reduce training and labor costs but at same requiring the best "talent " for the job. Our account managers will assist in managing fluctuating skill needs, gaps and changing staffing needs to meet a company's need and timelines. GCM is also a hardware and software company that works hard to align companies and individuals with the right products or services to meet their needs.

Company details

Company typeTPE

IndustryHuman Resources, Staffing & Recruiting

Company size11 - 50

Links

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Job description

Remote AI Architect needs 10+ years' experience enterprise-wide AI programs or platform buildouts.

AI Architect requires:

Strong understanding of data governance, privacy, security, and model risk management.
Prior experience with large-scale transformation programs.
equired Qualifications
Bachelor's degree in Computer Science, Engineering, or a related technical field.
5+ years of experience in application development, engineering, or solution delivery roles.
1+ years of hands-on experience in AI/ML engineering, data science, or AI solution architecture.
Strong hands-on experience with machine learning frameworks and LLM platforms (e.g., OpenAI, Azure AI Foundry, Copilot Studio/Agent Builder, or comparable generative AI ecosystems).
Deep expertise in cloud platforms, particularly Microsoft Azure, and modern architectural patterns (microservices, event-driven architectures, API-first design).
Proficiency in one or more of the following: Python, Azure Machine Learning, or related AI/ML tooling.
Experience with MLOps/LLMOps ecosystems, including tools such as MLflow, Kubernetes, LangChain, vector databases, and feature stores.
Strong hands on experience with ML frameworks, LLM platforms - OpenAI, MSFT/Azure Cloud foundry, Copilot Studio Agent builder, low code/no code platforms, and generative AI tools.
Background in RAG systems, model fine tuning, embeddings, vector storage, and retrieval optimization.

AI Architect duties:

Provide architectural oversight across AI/ML projects to ensure consistency, performance, and maintainability.

Evaluate and select AI technologies, frameworks, cloud services, vector databases, LLM orchestration frameworks, and tooling.

Support development teams on model selection, training pipelines, prompt engineering, fine tuning, RAG (Retrieval-Augmented Generation), and evaluation methodologies.

Mentor engineers, analysts, and product teams on AI best practices.