Job Description
Job Description: Infrastructure Architect (Full-Stack, AI & Platform Engineering)
Location: Hybrid / Onsite / Remote
Experience Required: 10 to 12 Years (Minimum 8 Years in Infrastructure Architect Role)
Department: Enterprise Architecture / Engineering
Role Overview
We are seeking an experienced Enterprise Architect to lead the design and implementation of scalable, high-performance enterprise platforms. The ideal candidate will have deep expertise in full-stack development, AI/ML systems, Python, and modern cloud-native architectures. This role requires strong experience in system design, scalability, CI/CD, and enterprise integrations.
Key Responsibilities
Define and drive enterprise architecture strategy and roadmap
Design scalable, resilient, and high-performance systems
Architect full-stack applications (frontend + backend)
Lead AI/ML and Agentic AI platform architecture
Design and optimize RAG pipelines and data systems
Define system integration patterns across enterprise tools
Drive CI/CD, DevOps, and automation strategies
Ensure system scalability, sizing, and performance optimization
Collaborate with stakeholders for solution architecture
Establish best practices, standards, and governance
Mentor engineering teams and review technical designs
Required Skills & Qualifications
6+ years of software development experience
Minimum 5 years in architect or senior technical leadership role
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Strong expertise in Python and backend systems
Experience in full-stack development (React or similar)
Deep understanding of system design and distributed architecture
Hands-on experience with AI/ML and Agentic AI systems
Strong knowledge of RAG, LLMs, and vector databases
Experience with CI/CD pipelines and DevOps practices
Proficiency with GitHub and Agile tools (JIRA)
Experience with cloud platforms (AWS/Azure/GCP)
Architecture & Technical Expertise
Microservices and event-driven architecture
API design and integration patterns
Scalability, load balancing, and system sizing
Containerization (Docker) and orchestration (Kubernetes)
Observability, monitoring, and logging
Security, compliance, and governance in enterprise systems
Good to Have
Experience in enterprise platforms like ITSM or automation tools
Knowledge of AI governance and guardrails
Exposure to multi-agent orchestration frameworks
Cost optimization strategies for cloud and AI workloads
Leadership & Soft Skills
Strong leadership and mentoring capabilities
Strategic thinking and decision-making
Excellent communication and stakeholder management
Ownership and accountability mindset
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