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-productive, 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.

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.
- Support deployment of SLMs on GPUs, CPUs, NPUs, containers, Kubernetes, and edge devices.

RAG, Knowledge & Enterprise Data Integration
- Design RAG pipelines using vector databases, enterprise search, document stores, and knowledge graphs.
- Architect SLM-powered solutions that integrate structured, semi-structured, and unstructured enterprise data.
- Enable domain-specific retrieval, grounding, citations, and hallucination reduction mechanisms.
- Work with data engineering teams to define ingestion, chunking, indexing, metadata, and retrieval strategies.
- Integrate with enterprise systems such as CRM, ERP, ITSM, ECM, data lakes, collaboration tools, and APIs.

Stakeholder & Technical Leadership
- Work with business teams to identify use cases where SLMs provide better ROI than large language models.
- Translate business requirements into scalable AI solution architecture.
- Lead architecture reviews, proof-of-concepts, pilots, and productionization of SLM solutions.
- Mentor engineering teams on SLM design patterns, model optimization, and production AI practices.
- Contribute to AI platform roadmap, reference architectures, and reusable accelerators.

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.

Location: Pan India

📌 AI Architect- Model Engineering (India)
🏢 GK HR Consulting India Private
📍 India