Role Overview

We are seeking a highly accomplished AI Architect to lead the design, implementation, and governance of enterprise-scale AI platforms integrated with DevOps, Cloud, and Security frameworks.

This role requires a technologist capable of architecting production-grade AI/ML and GenAI solutions while embedding secure DevSecOps practices across multi-cloud environments. The ideal candidate combines deep AI expertise with strong cloud architecture, automation, and security leadership.

Key Responsibilities

AI & Architecture Leadership

Design and architect enterprise AI/ML and GenAI platforms (LLMs, RAG, agentic AI, AIOps, automation).

Define scalable AI reference architectures aligned with business objectives.

Lead end-to-end AI lifecycle management: model development, validation, deployment, monitoring, and governance.

Establish standards for AI explainability, observability, and ethical AI practices.

Cloud & Platform Engineering

Architect AI solutions across AWS, Azure, or GCP environments.

Design scalable data pipelines, model serving infrastructure, and distributed systems.

Implement containerization (Docker) and orchestration (Kubernetes).

Build high-availability, resilient AI platforms with performance optimization.

DevOps & MLOps Integration

Establish CI/CD pipelines for AI/ML workloads.

Implement Infrastructure as Code (Terraform, ARM, CloudFormation).

Build automated model deployment and monitoring pipelines (MLOps).

Integrate AI into DevSecOps frameworks for secure continuous delivery.

Security & Governance

Architect secure AI systems adhering to Zero Trust principles.

Implement model security controls (data protection, encryption, access control, secrets management).

Conduct threat modeling for AI workloads (prompt injection, model poisoning, drift).

Ensure compliance with enterprise security, regulatory, and audit requirements.

Collaborate with security teams to perform red-teaming and AI risk assessments.

Stakeholder & Strategic Leadership

Work closely with stakeholders to define AI transformation roadmaps.

Provide architectural governance and technical mentorship to engineering teams.

Evaluate emerging AI technologies and define adoption strategies.

Drive innovation initiatives aligned with enterprise modernization goals.

Required Qualifications

3+ years of experience in enterprise architecture, cloud engineering, or platform leadership.

3+years designing and deploying AI/ML or GenAI solutions in production.

Strong expertise in Python, AI frameworks (TensorFlow, PyTorch, LangChain, etc.).

Deep understanding of LLM architecture, RAG systems, and agentic frameworks.

Hands-on experience with Kubernetes, Docker, CI/CD pipelines.

Strong cloud architecture experience (AWS/Azure/GCP certifications preferred).

Experience implementing DevSecOps practices.

Strong knowledge of enterprise security frameworks and cloud security controls.

Experience designing high-availability distributed systems.

Preferred Qualifications

Experience building enterprise AI platforms (AIOps, self-healing systems, automation).

Knowledge of data governance and enterprise knowledge graphs.

Experience integrating AI with ITSM platforms (ServiceNow, Remedy).

Cloud or Security certifications (AWS/Azure Architect, CISSP, CCSP, etc.).

Experience leading global, cross-functional technical teams.

Leadership Competencies

Strategic thinking and enterprise vision.

Strong executive communication skills.

Ability to translate complex AI concepts into business value.

Governance-driven mindset with innovation orientation.

Systems Integration Specialist