Job Description :

We are seeking a highly experienced Generative AI Architect to lead the design, architecture, and solutioning of enterprise-grade GenAI platforms and applications.

Total Experience : 8 - 14 years

Key Responsibilities :

Architecture & Solution Design :

- Architect end-to-end GenAI solutions, including data pipelines, model selection, LLM fine-tuning, RAG frameworks, orchestration, and deployment.

- Design scalable, secure, and cost-optimized GenAI reference architectures on Azure/AWS/GCP.

- Define solution blueprints integrating LLMs, vector DBs, data lakes, enterprise APIs, and microservices.

- Evaluate and select appropriate foundation models (OpenAI, Anthropic, Meta, Google, etc.) based on business needs.

Technical Leadership :

- Provide architectural governance and best practices across multiple GenAI initiatives.

- Guide engineering teams on model integration, optimization, evaluation, and MLOps/LLMOps.

- Drive PoCs, feasibility studies, and technology assessments.

RAG & LLM Engineering :

- Architect Retrieval-Augmented Generation (RAG) systems using vector stores (Pinecone, FAISS, Weaviate, etc.)

- Optimize prompt engineering, model evaluation, grounding, hallucination reduction, and response accuracy.

- Implement model fine-tuning, domain adaptation, and performance monitoring.

Data Engineering & Security :

- Design data ingestion, governance, and preprocessing pipelines for structured, unstructured, and multimodal data.

- Ensure compliance with enterprise security, privacy, model safety, and responsible AI frameworks.

- Collaborate with data engineering teams to integrate with enterprise data platforms.

Stakeholder Engagement & Delivery :

- Work with business leaders to identify GenAI use cases, define roadmaps, and build ROI-driven solutions.

- Prepare and deliver solution proposals, architecture documents, technical presentations, and cost estimates.

- Collaborate with product, engineering, data science, and cloud teams for end-to-end delivery.

Required Skills & Experience :

Core Technical Skills :

- 8 - 14 years of experience in AI/ML, cloud architecture, or enterprise software engineering.

- 3 - 5 years hands-on experience in LLMs / GenAI platforms.

Tech Stack :

- LLMs (OpenAI, GPT, Claude, Gemini, Llama, etc.)

- GenAI frameworks : LangChain, LlamaIndex, HuggingFace

- RAG architecture, vector databases, embeddings

- Cloud platforms : AWS (Bedrock/SageMaker), Azure (OpenAI/ML), GCP (Vertex AI)

- Python, PyTorch, TensorFlow, REST, GraphQL

- CI/CD, MLOps/LLMOps, containerization (Docker, Kubernetes)

Architecture & Solutioning Skills :

- Enterprise architecture (TOGAF is a plus).

- Building scalable, distributed microservices.

- Design of secure AI systems with RBAC, encryption, data masking, model governance.

Soft Skills :

- Strong communication and executive-level presentation skills.

- Ability to translate complex technical concepts into business-friendly language.

- Proven leadership in multi-functional teams.

Preferred Qualifications :

- Master's degree in Computer Science, Engineering, AI/ML, or related field.

- Certification in cloud architecture (AWS/Azure/GCP).

- Experience in multimodal AI, agents, or advanced model fine-tuning.

- Prior experience as an AI architect or lead ML engineer.

Why Join Us :

- Lead strategic AI transformation initiatives for global clients.

- Work with cutting-edge GenAI tools, models, and frameworks.

- Opportunity to influence AI strategy and enterprise roadmaps