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Mid-senior specialized architect with GenAI skills reduces applicant pool, but metro location and hybrid model increase competition.
Strong architecture fundamentals transfer across industries, but GenAI and cloud specifics raise moderate domain bias.
Requires deep Node.js/Python, cloud, IaC, Kubernetes, and GenAI expertise, enforcing strict technical filters.
Own end-to-end solution architecture including requirement analysis, design, build, and production support for client projects.
Define and enforce architecture standards; lead technical discovery and solutioning including pre-sales activities and architecture reviews.
Architect backend systems using Node.js and Python, design secure and scalable cloud architectures on AWS/Azure/GCP, and integrate Generative AI capabilities into solutions.
Strong hands-on experience with Node.js and Python backend development including REST/GraphQL APIs and microservices.
Practical architecture and hands-on experience with at least one cloud platform: AWS, Azure, or GCP, including IaC tools like Terraform or CloudFormation.
Working knowledge of Generative AI technologies including LLM ecosystems, vector databases, prompt and agentic engineering techniques.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in distributed system design and cloud-native application architecture with multi-cloud exposure preferred.
Proven ability to lead technical solutioning and governance in client-facing roles including pre-sales and technical audits.
Familiar with modern container orchestration (Docker, Kubernetes) and complex backend data architectures (SQL and NoSQL) at scale.