Job Title : AI Architect - Generative AI.

Experience : 8-10 Years.

Location : Remote (Contractual Role).

Duration : 12 months.

Type : Contract (Full-time/Part-time - depending on your need).

Job Summary :

We are seeking a highly experienced AI Architect with a strong background in AI/ML systems architecture and Generative AI technologies to lead the design and implementation of innovative, AI-driven solutions.

The ideal candidate will be responsible for driving end-to-end AI architecture, with a strong focus on LLMs, transformer models, embeddings, RAG pipelines, and deploying enterprise-ready AI applications at scale.

Key Responsibilities :

- Design, develop, and oversee scalable AI/ML architectures across cloud and hybrid environments.

- Lead the implementation of Generative AI solutions, including LLM-based applications (e.g. , GPT, LLaMA, Claude).

- Architect and optimize Retrieval-Augmented Generation (RAG) pipelines and vector database integration.

- Collaborate with product, data science, and engineering teams to translate business requirements into robust AI systems.

- Evaluate and integrate open-source and commercial GenAI models (e.g. , Hugging Face, OpenAI, Anthropic).

- Establish best practices for model fine-tuning, prompt engineering, and AI safety/compliance.

- Drive PoC to production lifecycle for GenAI tools like chatbots, document summarizers, copilots, etc.

- Maintain technical documentation, governance frameworks, and model performance monitoring.

Must-Have Skills : .

- 8-10 years of experience in AI/ML development and architecture.

- Hands-on experience with Generative AI models like GPT, BERT, LLaMA, Claude, etc.

- Deep knowledge of LLMs, transformer architectures, embedding models, and fine-tuning techniques.

- Expertise in Python, TensorFlow/PyTorch, and Hugging Face Transformers.

- Experience with LangChain, LLM orchestration, and vector DBs like Pinecone, FAISS, or Weaviate.

- Solid understanding of cloud services (AWS/GCP/Azure), Kubernetes, and scalable model deployment strategies.

- Familiarity with MLOps practices, including CI/CD for ML, experiment tracking, and monitoring.

- Strong knowledge of data privacy, AI ethics, and responsible AI frameworks.

Preferred Skills : .

- Exposure to multi-modal models (vision + language).

- Experience deploying enterprise GenAI use cases (e.g. , document processing, customer support bots, knowledge assistants).

- Contributions to open-source GenAI frameworks or communities.

- Strong communication and stakeholder management skills.