HyrEzy Talent Solutions

AI Architects
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Department: Technology Architecture &amp; AI Practice
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Experience Required: 10+ Years (with deep architecture/leadership background)
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Compensation (Market Standard): INR 4,000,000 to 6,000,000 Per Annum (CTC)
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Locations: Bangalore / Pune / Hybrid / Remote-flexible across India
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Role Overview &amp; Key Responsibilities
We are seeking a visionary AI Architect to lead the design and implementation of enterprise-grade artificial intelligence and generative AI solutions. In this leadership position, you will define our core technical reference architectures, establish enterprise governance frameworks, and guide engineering teams through the complex transition from proof-of-concept to highly scalable, secure, and cost-effective production systems. You will champion best practices in LLMOps, model evaluation, and secure data handling.
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Enterprise Solution Architecture: Architect end-to-end AI systems, specifying cloud-native patterns, multi-tenant boundaries, high-availability compute layers, and scalable vector storage.
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Governance &amp; Standards: Formulate and enforce enterprise standards for AI safety, compliance, ethical data usage, access control, and prompt security frameworks.
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LLMOps &amp; Tooling Strategy: Define the strategy for model monitoring, latency optimization, cost control, caching mechanisms, and automated regression testing.
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Technical Leadership: Mentor senior engineers, drive complex code reviews, evaluate emerging AI models and frameworks, and partner with executive leadership on technical strategy.
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Cross-Functional Collaboration: Work closely with product management, security, and client delivery teams to ensure AI systems align tightly with business outcomes and regulatory mandates.
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Required Skills &amp; Experience
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Architecture Experience: 10+ years in software engineering with at least 4+ years dedicated specifically to architecting enterprise-scale AI, ML, and LLM implementations.
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Domain Knowledge: Comprehensive understanding of RAG patterns, fine-tuning strategies, vector embeddings, agentic architectures, and prompt security vulnerabilities.
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Cloud &amp; Infrastructure: Deep expertise in deploying containerized AI workloads across major cloud providers (AWS, GCP, or Azure) leveraging Kubernetes and modern DevOps pipelines.
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Strategic Mindset: Exceptional communication skills with a proven track record of presenting complex technical strategies to executive stakeholders and guiding cross-functional teams.
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