AI Architect

Job Title : AI Architect

Experience : 7–10 years (minimum 5+ years in AI / ML, with strong MLOps and cloud experience)

Location : Remote

Role Overview

We are seeking an experienced AI Architect to design and govern end‑to‑end AI and ML architectures across a variety of enterprise use cases (e.g., prediction, personalization, recommendation, anomaly detection, automation). The ideal candidate will operate as a strategic technical leader, defining AI solution blueprints on Azure and AWS and ensuring scalable, secure, and compliant AI systems across products and teams.

This role bridges business and technology by translating organizational objectives into robust AI architectures, reference patterns, and platform capabilities that can be reused across multiple domains and product lines.

Key Responsibilities

• Define and own end‑to‑end AI architecture for multiple enterprise use cases, including data flows, model lifecycle, and serving patterns across Azure and AWS.
• Design AI / ML solution blueprints covering data ingestion, feature stores, training pipelines, model registry, deployment, monitoring, retraining, and decommissioning.
• Establish and standardize MLOps frameworks (MLflow / Kubeflow / Airflow, Docker, Kubernetes) and reference implementations that AI / ML engineers and data scientists can reuse across teams.
• Collaborate with product, data, and business stakeholders to identify AI opportunities, shape solution options, and align AI architectures with business and non‑functional requirements (scalability, reliability, cost, latency).
• Define and enforce governance for model approval, explainability, versioning, drift monitoring, and compliance with data privacy and regulatory requirements relevant to the organization.
• Guide the selection and integration of cloud‑native services (Azure ML, AWS SageMaker, Lambda, EC2, S3, Azure Functions, API gateways, monitoring stacks) into cohesive AI platforms.
• Work closely with security, compliance, data, and enterprise architecture teams to ensure AI solutions meet standards for security, resilience, observability, and cost optimisation.
• Provide technical leadership and mentoring to AI engineers, ML engineers, and data scientists on best practices in AI architecture, MLOps, and cloud‑native design.
• Create and maintain architectural artefacts : high‑level designs, detailed solution diagrams, standards, and documentation for AI platforms and reference solutions.

Required Skills

Architecture & Leadership

AI / ML & MLOps

Cloud Platforms (Azure & AWS)

Governance, Security & Compliance

Tooling & Engineering Foundations

Preferred Qualifications