What are the responsibilities and job description for the AI Architect position at Jersey Technology Partners?
Job Description: AI Architect, 6 months Contract, NJ
Position Overview
The AI Architect is responsible for defining and implementing the enterprise architecture needed to support AI initiatives across the organization. This role combines strong technical expertise, strategic thinking, and business understanding to design scalable AI solutions, guide responsible adoption, and enable data-driven decision-making. Experience with cloud platforms, modern data architectures, and Microsoft AI tools is preferred.
Key Responsibilities
AI Strategy & Roadmapping
- Develop an enterprise AI strategy aligned with business priorities.
- Define architectural standards, patterns, and best practices for AI, ML, and automation solutions.
- Evaluate emerging AI technologies and recommend adoption where appropriate.
Solution Architecture & Design
- Architect end-to-end AI solutions, including data ingestion, model development, deployment, and monitoring.
- Design integration patterns between AI services, applications, and existing enterprise systems.
- Collaborate with data engineers, developers, and stakeholders to translate business needs into technical designs.
Model Development & Deployment
- Guide teams in building, training, and optimizing machine learning or large-language-model solutions.
- Establish MLOps practices for model lifecycle management, versioning, monitoring, and continuous improvement.
- Ensure AI solutions meet standards for scalability, reliability, and performance.
Data & Integration Architecture
- Partner with data teams to ensure data availability, quality, and structure for AI workloads.
- Support the design of data pipelines, data lakes, and structured/unstructured data integration.
- Leverage cloud services—such as Azure, AWS, or GCP—to implement scalable compute and storage architectures.
Responsible AI, Governance & Security
- Establish guidelines for the responsible and ethical use of AI.
- Support governance practices, including model documentation, validation, and risk mitigation.
- Ensure compliance with security, privacy, and regulatory requirements.
Collaboration & Leadership
- Serve as a subject-matter expert and advisor to business units evaluating AI use cases.
- Lead technical design reviews, proof-of-concept projects, and platform evaluations.
- Mentor engineering teams on best practices in AI, automation, and modern software architecture.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
- 10 years of experience in AI/ML engineering, data engineering, cloud architecture, or software engineering.
- Experience with at least one major cloud AI ecosystem (Azure, AWS, or GCP).
- Familiarity with Microsoft technologies such as:
- Foundry
- Azure AI Services or Azure Machine Learning
- Power Platform AI capabilities
- Microsoft 365 or Copilot integration concepts
- Strong understanding of data pipelines, APIs, vector search, and modern application integration.
Preferred Qualifications
- Experience designing AI solutions for enterprise environments.
- Microsoft, AWS, or GCP certifications.
- Understanding of LLM architectures, prompt engineering, or retrieval-augmented generation (RAG).
- Experience in model monitoring, drift detection, and MLOps tooling.