Enterprise Architecture - Generative AI

Description :

We are looking for an accomplished Enterprise Architect with deep expertise in Generative AI, AI/ML platforms, cloud architecture, and enterprise transformation. The ideal candidate will define the AI-driven technology roadmap, design scalable architectures, and lead the integration of advanced GenAI capabilities across the enterprise landscape.

Key Responsibilities :

1. Enterprise Architecture & Strategy :

- Develop and maintain enterprise architecture blueprints, reference models, and technology roadmaps.

- Align architecture strategy with business goals, ensuring long-term scalability and flexibility.

- Drive digital transformation initiatives using modern cloud and AI capabilities.

2. Generative AI Architecture :

- Lead the design and deployment of GenAI solutions, including LLM-based applications, AI copilots, RAG systems, intelligent automation, and conversational AI platforms.

- Evaluate and integrate models such as GPT, Llama, Claude, Gemini, or enterprise fine-tuned LLMs.

- Architect secure and scalable AI pipelines, including model training, fine-tuning, inference optimization, and prompt engineering.

- Work with vector databases, embeddings, retrieval systems, and knowledge graph integrations.

3. AI/ML & Data Ecosystem :

- Collaborate with data engineering teams to define data pipelines, MLOps, feature stores, and governance frameworks.

- Implement AI governance, responsible AI principles, auditing, and data privacy controls.

- Ensure enterprise readiness for AI adoptionperformance, security, compliance, and scalability.

4. Cloud Architecture :

- Architect AI and enterprise workloads on Azure / AWS / GCP.

- Utilize cloud-native AI technologies such as Azure OpenAI, AWS Bedrock, GCP Vertex AI, etc.

- Drive cloud modernization, optimization, and application transformation.

5. Solution Architecture & Integration :

- Provide architectural leadership for large cross-functional initiatives.

- Evaluate and define AI integration patterns across enterprise applications (ERP, CRM, BPM, legacy systems).

- Define API, microservices, and event-driven integration strategies.

6. Governance & Best Practices :

- Own enterprise-wide architecture governance, design reviews, and compliance assessments.

- Develop and enforce architecture standards, reusable patterns, and best practices.

- Support risk assessments, security evaluations, and technology audits.

7. Stakeholder & Leadership Engagement

- Work with CXOs, product owners, and engineering teams to drive AI-first architectural decisions.

- Present architectural recommendations clearly to technical and non-technical audiences.

- Mentor engineering and architecture teams in AI and cloud design principles.

Required Skills & Experience :

Technical Expertise :

- Strong background in enterprise architecture frameworks (TOGAF, Zachman, ArchiMate).

- Deep hands-on experience with GenAI technologies, including :

- LLMs, RAG, prompt engineering

- Model fine-tuning & optimization

- Vector databases (Pinecone, Milvus, FAISS, Chroma, etc.)

- LangChain, LlamaIndex, or other orchestration frameworks

- Strong understanding of AI/ML lifecycle, MLOps, and data engineering.

- Expertise in microservices, API architecture, event-driven systems.

- Hands-on cloud experience with Azure/AWS/GCP.

- Understanding of cybersecurity, IAM, and zero-trust principles.

Soft Skills :

- Excellent presentation and communication skills.

- Ability to influence senior stakeholders.

- Strong analytical and conceptual thinking.

- Ability to lead architecture discussions and drive consensus.

Preferred Qualifications :

- Certifications : TOGAF, Azure Solutions Architect, AWS SA Pro, Google Professional Cloud Architect.

- Experience implementing enterprise-scale GenAI solutions.

- Exposure to ERP systems (SAP, Oracle), CRM, data platforms, and integration tools.