Systems Integration Specialist

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.
  
  

• 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.
  
  

• 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.
  
  

• 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.
  
  

• 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.
  
  

• 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.
  
  

• 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.
  
  

• Strategic thinking and enterprise vision.
• Strong executive communication skills.
• Ability to translate complex AI concepts into business value.
• Governance-driven mindset with innovation orientation.