Sr. AI Technology Architect
Role details
Job location
Tech stack
Job description
- Define and govern enterprise AI architecture including LLMs, RAG, Agentic AI, and Edge AI systems.
- Establish reference architectures for cloud-native AI, GPU-based inferencing, and distributed workloads.
- Architect and deploy LLM-powered solutions using RAG, embeddings, vector databases, and orchestration frameworks.
- Design Agentic AI workflows leveraging tools such as LangChain, LangGraph, Azure AI, and Databricks.
- Lead AI infrastructure strategy including GPU optimization and high-performance compute environments.
- Build and scale AI platforms across AWS, Azure, and Google Cloud Platform ecosystems.
- Lead development of advanced AI/ML models across NLP, computer vision, graph ML, and forecasting domains.
- Architect Edge AI solutions for low-latency, distributed decision-making systems.
- Establish governance for responsible AI, security, and compliance.
- Mentor teams and drive innovation and capability development.
Requirements
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15+ years of experience in AI/ML, Data Science, or Technology Architecture.
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Strong expertise in Generative AI, LLMs, RAG, and Agentic AI systems.
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Proficient in Python, APIs, microservices, and data engineering frameworks.
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Experience with cloud platforms (AWS, Azure, Google Cloud Platform) and containerization technologies.
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Deep understanding of AI infrastructure including GPU optimization and benchmarking.
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Proven ability to lead large-scale transformation programs. Preferred Qualifications & Experience
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Experience in banking, telecom, healthcare, energy, or supply chain domains.
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Exposure to Edge AI, O-RAN architectures, and distributed systems.
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Advanced degree (PhD/Master's) in AI, Data Science, or related field.
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Experience in Enterprise adoption of AI platforms and architecture standards.
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Experience in Scalable deployment of AI solutions delivering measurable outcomes.