- Company Name
- Jersey Technology Partners
- Job Title
- AI Architect
- Job Description
-
**Job Title:** AI Architect
**Role Summary:**
Design and deliver enterprise‑wide AI architecture that aligns with business strategy. Lead end‑to‑end AI solution development, from data ingestion to model deployment, ensuring scalable, secure, and responsible AI practices across the organization.
**Expactations:**
- Own AI strategy, road‑mapping, and architectural standards.
- Deliver comprehensive solution designs and oversee implementation.
- Champion responsible AI, governance, and cybersecurity compliance.
- Mentor cross‑functional teams and influence AI adoption decisions.
**Key Responsibilities:**
- **AI Strategy & Roadmapping:** Develop enterprise AI strategy tied to business priorities; evaluate and recommend emerging AI technologies.
- **Solution Architecture & Design:** Architect end‑to‑end AI pipelines, integration patterns with enterprise systems, and scalable deployment architectures.
- **Model Development & Deployment:** Guide ML/LLM training, optimization, and MLOps practices; enforce model lifecycle management, versioning, and monitoring.
- **Data & Integration Architecture:** Partner with data teams to build data ingestion pipelines, data lakes, and structured/unstructured data integration using Azure, AWS, or GCP.
- **Responsible AI & Governance:** Establish ethical guidelines, model documentation, validation, risk mitigation, and compliance with security, privacy, and regulatory requirements.
- **Collaboration & Leadership:** Serve as subject‑matter expert, lead design reviews, proof‑of‑concepts, and platform evaluations; mentor engineering teams on best practices.
**Required Skills:**
- Enterprise AI strategy & architecture design.
- End‑to‑end AI solution development (data, model, deployment).
- MLOps (CI/CD, monitoring, drift detection).
- Cloud AI ecosystems – Azure AI services, Azure Machine Learning, AWS AI, or GCP AI.
- Microsoft technologies: Foundry, Azure AI/ML, Power Platform AI, Microsoft 365/Copilot concepts.
- Data pipelines, APIs, vector search, and modern application integration.
- Responsible AI governance, data privacy, security, and regulatory compliance.
**Required Education & Certifications:**
- Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field.
- 10+ years of experience in AI/ML engineering, data engineering, cloud architecture, or software engineering.
- Certifications: at least one major cloud AI ecosystem (Microsoft Certified: Azure AI Engineer Associate, AWS Certified Machine Learning – Specialty, or GCP Professional Machine Learning Engineer).
- Additional certifications in MLOps, data engineering, or security are a plus.
East brunswick, United states
On site
Senior
12-12-2025