Job Description

Role Purpose

We are looking for an experienced AI Architect- Model Engineering to design, build, and govern enterprise-grade solutions using Small Language Models for domain-specific AI applications. The role requires strong expertise in AI/ML architecture, model architecture optimization, cloud-native deployment, data pipelines, RAG, fine-tuning, model evaluation, and secure enterprise integration. 

The ideal candidate will architect lightweight, cost-efficient, secure, and scalable AI systems that can run across cloud, private cloud, on-premise, or edge environments. The architect will work closely with AI Engineers, Data Scientists, Cloud Architects, Product Owners, and Business SMEs to deliver practical GenAI solutions optimized for enterprise use cases. 

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Key Responsibilities 

Model Architecture & Strategy 

• Define enterprise architecture patterns for Small Language Model-based applications.
• Evaluate and recommend suitable Models  based on accuracy, latency, cost, privacy, domain fit, and deployment constraints.
• Design AI solutions using open-source and commercial SLMs such as Phi, Llama, Mistral, Gemma, Qwen, Falcon, or domain-specific models.
• Establish architectural standards for SLM selection, adaptation, deployment, monitoring, and governance.
• Build reusable blueprints for SLM-based assistants, copilots, workflow agents, document intelligence, and enterprise search.

• Model Adaptation & Optimization

  • Architect solutions involving prompt engineering, RAG, fine-tuning, LoRA, QLoRA, distillation, quantization, and model compression.
  • Define when to use prompt-only, RAG-based, fine-tuned, or hybrid approaches.
  • Optimize SLMs for low latency, reduced inference cost, and domain-specific accuracy.
  • Guide teams on token optimization, context management, embeddings, reranking, and model evaluation.

• Preferred Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, Engineering, or related field.
  • 8+ years of experience in software architecture, cloud architecture, or AI/ML engineering.
  • 3+ years of hands-on experience with NLP, transformers, GenAI, or LLM-based applications.
  • Experience deploying AI models in regulated or enterprise environments.

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