Senior AI Architecture Specialist

Job Summary
We are looking for a highly experienced Senior AI Architecture Specialist to lead the design, development, and deployment of enterprise-grade AI solutions. This role will be responsible for architecting scalable AI-enabled platforms, integrating cloud-native AI services, and driving best practices across AI engineering, DevOps, and secure application development.
The ideal candidate will have deep expertise in enterprise AI architecture, strong hands-on experience with Microsoft Azure AI services, and the ability to guide engineering teams in building reliable, scalable, and secure AI-driven applications aligned with business objectives.

Key Responsibilities
AI Solution Architecture & Design
Lead end-to-end architecture for enterprise AI platforms and intelligent applications
Design scalable, resilient, and secure AI-enabled systems using cloud-native patterns
Define architecture standards, reusable components, and best practices for AI integration
Evaluate and recommend AI frameworks, services, and architectural patterns

AI Integration & Platform Engineering
Integrate AI capabilities into existing and new enterprise applications
Architect solutions leveraging Azure AI ecosystem including LLM-based services, search, and cognitive APIs
Design microservices-based AI platforms with strong API governance
Ensure high availability, scalability, and performance optimization of AI workloads

Cloud Architecture & DevOps Enablement
Design and implement scalable cloud architectures on Microsoft Azure
Establish CI/CD pipelines and automation strategies for AI application lifecycle
Manage production deployment, migration, and lifecycle of AI infrastructure
Implement observability, monitoring, and performance tuning strategies

Security, Governance & Optimization
Conduct architecture and code reviews with a focus on performance, scalability, and security
Implement secure coding practices and enterprise security controls for AI workloads
Optimize cost, latency, and resource utilization across AI deployments
Define governance frameworks for AI platform reliability and maintainability

Leadership & Collaboration
Mentor development teams and provide technical leadership across projects
Collaborate with product managers, business stakeholders, and engineering teams
Drive adoption of modern AI engineering practices across the organization
Support architectural decision-making and technical roadmap planning

Mandatory Skills
Hands-on experience with Azure AI ecosystem including Azure OpenAI, AI Search, and Cognitive Services
Strong AI solution architecture and system integration experience
Expertise in full-stack development (backend and frontend frameworks)
Proven experience designing scalable cloud-native architectures on Azure
Advanced knowledge of DevOps practices, CI/CD pipelines, and automation
Strong experience with microservices architecture and API integration
Experience deploying and migrating AI workloads in production environments
Knowledge of secure coding practices and application security principles

Technical Skills
Azure OpenAI and Azure AI Services
Cognitive Services and AI Search platforms
Full-stack frameworks and API development
Containerization and orchestration (Docker, Kubernetes preferred)
DevOps automation and CI/CD pipelines
Cloud architecture and infrastructure design

Qualifications
Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related field
Minimum 7+ years of experience in software engineering, solution architecture, or AI platform development
Proven experience delivering AI-enabled enterprise applications

Soft Skills
Strong leadership and mentoring capability
Excellent communication and stakeholder management skills
Analytical thinking and structured problem-solving approach
Ability to work effectively in cross-functional and distributed teams

Good to Have
Experience in enterprise AI platform migration and modernization
Exposure to large-scale AI transformation initiatives
Knowledge of AI governance, monitoring, and evaluation frameworks