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Generative AI Architect

Job in 243601, Gurgaon, Uttar Pradesh, India
Listing for: True Tech Professionals
Full Time position
Listed on 2026-02-27
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Engineer
Job Description & How to Apply Below
Job Title:

Generative AI Architect

Location:

Gurgaon (Hybrid)

Experience:

8+ Years (3 Years in Generative AI)

Employment Type:

Full-Time

Role Overview
We are seeking a highly experienced  Generative AI Architect  to lead the design and implementation of enterprise-grade AI solutions powered by Large Language Models (LLMs), Transformer architectures, and advanced retrieval systems.
The ideal candidate will be responsible for defining AI architecture strategy, building scalable GenAI platforms, and driving innovation in areas such as RAG systems, semantic search, intelligent automation, and AI-driven personalization.
This is a high-impact leadership role requiring deep technical expertise, strong architectural vision, and stakeholder collaboration.

Key Responsibilities
AI & LLM Architecture Strategy
Define and lead the enterprise architecture for Generative AI solutions.
Design scalable, secure, and cost-efficient LLM-based systems.
Evaluate and select foundation models (Open-source / Commercial APIs).
Define governance, safety, and compliance standards for AI usage.
Large Language Model & RAG Systems
Architect and implement Retrieval-Augmented Generation (RAG) pipelines.
Design vector search architecture using embedding models and vector databases.
Lead fine-tuning strategies (LoRA, PEFT, full fine-tuning).
Optimize inference performance using quantization and model distillation.
Drive prompt engineering standards and reusable prompt frameworks.
Intelligent Search & Recommendation Systems
Architect semantic search, dense retrieval, and ranking pipelines.
Improve personalization and contextual recommendation engines.
Define evaluation metrics such as NDCG, Recall, CTR, Perplexity, and Latency.
⚙ AI Platform & MLOps
Design end-to-end ML lifecycle pipelines (training, validation, deployment).
Implement CI/CD for ML workflows.
Establish model monitoring, observability, and retraining frameworks.
Ensure scalability using Docker, Kubernetes, and distributed systems.
☁ Cloud & Infrastructure
Architect AI solutions on AWS, GCP, or Azure.
Design GPU infrastructure strategy and cost optimization models.
Work with distributed training and inference architectures.
Data Strategy & Governance
Define data architecture for training and retrieval pipelines.
Ensure data quality, compliance, and privacy standards.
Collaborate with Data Engineering to build scalable feature stores.
Leadership & Stakeholder Engagement
Lead cross-functional AI initiatives across Engineering, Product, and Business.
Present architectural designs to executive stakeholders.
Mentor AI/ML engineers and drive best practices.
Required Technical Qualifications
8+ years of experience in Software Engineering / ML / AI.
3+ years of hands-on experience in Generative AI and LLM systems.
Strong expertise in Python and deep learning frameworks (PyTorch / Tensor Flow).
Deep experience with Transformer architectures (BERT, GPT-family, encoder/decoder models).
Hands-on experience with:
Hugging Face
Lang Chain
Llama Index
Vector databases (FAISS, Pinecone, Milvus, Weaviate)
Strong knowledge of RAG system design and dense retrieval architectures.
Experience designing production-grade search or recommendation systems.
Expertise in cloud platforms (AWS/GCP/Azure).

Experience with MLOps tools (MLFlow, Kubeflow, Docker, Kubernetes).
Strong understanding of system design, distributed computing, and scalable architecture.

Preferred Qualifications

Experience with model quantization and optimization (ONNX, Tensor

RT).
Knowledge of Responsible AI, fairness, bias mitigation, and governance frameworks.
Experience building multi-modal AI systems (text + vision).
Exposure to enterprise AI adoption strategy.
Key Skills
Generative AI | LLM Architecture | RAG | Transformer Models | Vector Search | Prompt Engineering | LoRA | MLOps | Cloud AI | AI Governance | Semantic Search | AI System Design
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