The Role:
We are seeking a GenAI Architect—a seasoned Solution or Platform Architect—to take the lead in integrating intelligent automation, large language models (LLMs), and agentic systems into our core business. You will define the standards for how they scale AI capabilities across customer-facing products and internal operations, driving the transformation into an AI-first enterprise.
Key Responsibilities:
You will be the key architect defining and enabling our intelligent solutions across the enterprise.
- GenAI Strategy & Roadmap: Define the enterprise-wide GenAI and broader AI architecture roadmap, aligning it with our core data and digital strategy.
- Solution Leadership: Lead the design of solutions that seamlessly embed LLMs, GenAI, and agentic automation into mission-critical business workflows.
- Data Integration: Architect solutions that connect diverse structured and unstructured platforms (e.g., Databricks, Microsoft 365, SharePoint, Salesforce, Workday, Guidewire) to feed our AI pipelines.
- Operational Excellence: Partner with engineering teams to enable and govern LLMOps and AgenticOps, covering prompt lifecycle management, observability, caching, and model governance.
- Use Case Generation: Collaborate with business partners to shape high-impact use cases for intelligent summarization, classification, triage, and advisory systems.
You must be a hands-on architect with a strong foundation in enterprise systems and a clear focus on emerging AI patterns
- Architecture Expertise: Strong solution architecture experience across cloud, data integration (API/messaging), and enterprise applications in a large-scale environment.
- GenAI Patterns: Proven experience with Generative AI application patterns, specifically Retrieval-Augmented Generation (RAG) and agent-based architectures.
- Cloud Stack Proficiency: Working knowledge of Azure-native services is essential, including Azure OpenAI, Azure ML, Cognitive Search, and Azure Databricks.
- Responsible AI: Understanding of AI governance frameworks (e.g., ISO/IEC 42001, NIST AI RMF, EU AI Act) and ethical principles for AI design.
- Data Security: Expertise in secure architectural patterns for data access, classification, and masking of both structured and unstructured data.
Working Days:
Our hybrid model requires 40% office attendance (2 days/week) with a future move to 60% (3 days/week) to ensure strong collaboration and team cohesion.
