Job ID: 1231
Role Overview
The AI/MLops Architect is a senior leadership position focused on the design and operationalization of scalable, production-ready AI/ML architectures across diverse business units. In the rapidly evolving landscape of 2026, this role is critical for moving organizations from experimental proof-of-concept (POC) stages to a state of repeatable, governed, and high-performance delivery of machine learning models. You will serve as a hands-on architectural leader with significant influence across product, engineering, data, and security teams, ensuring that AI initiatives are not just innovative but also robust and secure.
Key Responsibilities
- Define and implement the end-to-end AI/ML reference architecture, covering the entire lifecycle from data injection through model serving and real-time monitoring.
- Establish enterprise standards for data storage, access patterns, and lineage, ensuring a clear separation between raw, curated, and feature-ready data.
- Assess and integrate shared platform capabilities such as feature stores, model registries, AI/ML catalogs, and experiment tracking systems.
- Design for scale across multiple business units, accounting for varying data sensitivity, regulatory requirements, and operational needs.
- Define standard development, validation, and production environments for AI/ML workloads to ensure consistency across the organization.
- Design repeatable ML delivery pipelines that include model training, validation, approval, promotion, and deployment (batch and real-time).
- Establish CI/CD and continuous training (CT) best practices specifically tailored for machine learning systems.
- Define ‘production-readiness’ for AI/ML models, including rigorous testing, validation, monitoring, and alerting patterns.
- Partner with security, legal, and compliance teams to integrate governance frameworks that ensure models are discoverable, auditable, and traceable without slowing down delivery.
- Create a ‘paved road’ for AI development by providing shared standards, templates, and tooling that allow business units to self-serve.
Technical Requirements
- Minimum of 10 years of experience in software engineering, data platforms, or machine learning engineering.
- At least 5 years of hands-on experience specifically deploying machine learning systems into production environments at scale.
- Proven expertise in designing comprehensive AI/ML platforms or MLOps architectures, rather than just individual models.
- Deep understanding of the ML lifecycle management, including data pipelines and feature engineering.
- Extensive experience with model serving patterns, including batch processing, real-time APIs, and edge deployment.
- Strong ability to communicate complex architectural designs and decisions to both technical and non-technical stakeholders.
- Experience working across organizational boundaries to align multiple business teams and units.
Preferred Qualifications
- Experience designing or operating feature stores and experiment tracking platforms.
- Familiarity with AI governance and risk frameworks in highly regulated or data-sensitive environments.
- Expertise in cloud-native ML platforms and infrastructure such as AWS SageMaker, Google Vertex AI, or Azure Machine Learning.
- Background in establishing standards and monitoring teams at an enterprise scale.
Success Metrics (12-18 Months)
- A fully documented and adopted AI/ML reference architecture utilized across all business units.
- Standardized environments and pipelines that significantly accelerate the promotion of models from POC to production.
- Measurable reduction in the duplication of feature engineering and model deployment efforts.
- Consistent visibility into the performance and operational health of all models running in production.
- Increased organizational confidence in the ability to deliver AI responsibly and at scale.
Special Requirements
Passport number is mandatory for submission. Candidates must hold H1b or H4EAD status only. Requires 10+ years of professional experience.
Compensation & Location
Salary: $195,000 – $275,000 per year (Estimated)
Location: Philadelphia, PA
Recruiter / Company – Contact Information
Recruiter / Employer: Agile Enterprise Solutions Inc.
Email: ibrahim@aesincus.com
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