GEN AI Architect

JD

• 14–18 years of proven experience in technology leadership / principal or application architect roles on enterprise-scale, distributed multi-tier systems.
• Strong architecture pedigree: n-tier, microservices, and event-driven architecture (EDA) design — including messaging/streaming platforms (Kafka or cloud-native equivalents) — enterprise integration, application maintenance and solution delivery, API design and management, and cloud-native delivery on AWS, Azure, or GCP (IaaS/PaaS/SaaS, containers, CI/CD).
• Deep expertise in at least one major enterprise stack (Java/Spring, .NET, Python, or Node.js) with breadth across others; working proficiency in Python for GenAI development.
• Demonstrable agentic GenAI delivery: at least one agent-assisted engineering or LLM-based solution taken into production or a serious enterprise pilot — able to walk through the architecture, trade-offs, and measured outcomes.
• Practical, current knowledge of multi-agent design, MCP, RAG variants (hybrid search with re-ranking, agentic RAG, RAG over code and structured data), embeddings/vector search, prompt and context engineering, evaluation harnesses and guardrails, and LLM limitations (hallucination, context-window constraints, cost/latency, data privacy).
• Experience modelling business domains and processes: ontologies, taxonomies, or knowledge graphs; state machines and lifecycle models; and the metadata practices that keep them current.
• Experience leading technology-driven programs — POCs, innovation initiatives, and solution asset development — through to large-scale delivery.
• Experience practicing Design Thinking and Systems Thinking in real-world scenarios.
• Outstanding client-facing communication: proven experience engaging customer stakeholders on requirements and delivery from an offshore model, and explaining complex technology in an easy-to-understand way.