Generative AI Architect
First seen by Alion on Sep 25, 2026.
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
Skills
Generative AI, LLM, LangChain, RAG, Python, Google Cloud Platform, Artificial Intelligence, AI Architecture, Machine Learning, VectorDB