Job Summary
We are seeking an experienced AI/ML Architect to lead the design and implementation of enterprise-scale Artificial Intelligence and Machine Learning solutions. The ideal candidate will define AI architecture, establish best practices, evaluate emerging AI technologies, and guide engineering teams in delivering scalable, secure, and production-ready AI platforms.
This role requires expertise in Machine Learning, Deep Learning, Generative AI, Large Language Models (LLMs), MLOps, cloud platforms, data engineering, and enterprise architecture.
Soft Skills
Strong technical leadership
Solution architecture expertise
Strategic thinking
Excellent communication and presentation skills
Stakeholder management
Mentoring and coaching
Problem-solving and analytical skills
Agile/Scrum leadership
Preferred Certifications
AWS Certified Machine Learning – Specialty
AWS Certified Solutions Architect – Professional
Microsoft Certified: Azure AI Engineer Associate
Microsoft Certified: Azure Solutions Architect Expert
Google Professional Machine Learning Engineer
Google Professional Cloud Architect
Databricks Certified Machine Learning Professional
Kubernetes Certified Application Developer (CKAD)
Key Responsibilities
Design enterprise AI/ML architecture and technical roadmaps.
Lead the architecture and implementation of Machine Learning and Generative AI solutions.
Design scalable AI platforms supporting model training, deployment, monitoring, and governance.
Architect Retrieval-Augmented Generation (RAG) solutions using vector databases.
Design AI-powered applications leveraging LLMs and foundation models.
Define AI governance, security, compliance, and Responsible AI frameworks.
Lead model lifecycle management using MLOps best practices.
Collaborate with business leaders to identify AI opportunities and define solution strategies.
Guide engineering teams through architecture reviews, code reviews, and technical mentorship.
Optimize AI solutions for scalability, latency, cost, and reliability.
Evaluate and recommend AI technologies, frameworks, and cloud services.
Establish enterprise AI standards, reusable frameworks, and best practices.
Support pre-sales activities, solution proposals, and client presentations where applicable.