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AI Architect
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Work Location: Chennai
Education Qualification: Bachelor’s Degree
Experience: 10-12 years
Required Skills:
Architecture & Design
- Define end-to-end architecture for GenAI & Agentic AI solutions
- Design scalable and secure AI pipelines including data ingestion, model training, fine-tuning, deployment, and monitoring.
- Architect multi-agent AI systems leveraging frameworks like LangChain, AutoGen, LlamaIndex, or similar.
Hands-on Development
- Build and optimize AI applications in Python using frameworks such as PyTorch, TensorFlow, Hugging Face Transformers.
- Implement and integrate LLMs, embeddings, RAG (Retrieval-Augmented Generation), vector databases (Pinecone, FAISS, Weaviate, Milvus).
- Develop autonomous AI agents for workflow automation, reasoning, and decision-making.
Innovation & Strategy
- Evaluate and recommend emerging GenAI & Agentic AI frameworks, tools, and platforms.
- Define best practices for prompt engineering, model fine-tuning, safety, compliance, and governance.
- Collaborate with stakeholders to align AI solutions with business goals and enterprise architecture.
Leadership & Mentoring
- Lead technical discussions and provide architectural guidance to engineering teams.
- Mentor data scientists, ML engineers, and software developers in AI best practices.
- Collaborate with product managers and business leaders on solution roadmaps.
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Name
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Tell me about your most complex end-to-end AI platform you designed and deployed. What were the main components, data flow, and the measurable business impact?
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How do you implement ML lifecycle and MLOps in production? Include CI/CD for models, model registry, reproducibility, and monitoring.
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What is your approach to data governance, privacy, and compliance in AI projects?
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How do you balance latency, throughput, accuracy, and cost in production AI systems?
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Can you share a time you influenced a critical architectural decision with stakeholders?
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