GenAI Architect

We are seeking an experienced GenAI Architect to design and implement scalable, secure, enterprise-grade Generative AI solutions. The ideal candidate will have strong expertise in AI architecture, LLMs, RAG, Agentic AI, and Google Cloud Platform (GCP), along with a solid software engineering and enterprise integration background.Key ResponsibilitiesDesign end-to-end GenAI architectures for enterprise products and applications.Develop and integrate LLM-powered solutions using RAG, embeddings, vector databases, and AI agents.Establish best practices for prompt engineering, model orchestration, inference, and AI application development.Integrate GenAI capabilities into existing enterprise platforms using APIs and microservices.Design scalable AI workflows with model routing, fallback mechanisms, and performance optimization.Implement MLOps practices for model deployment, monitoring, versioning, and lifecycle management.Ensure AI security, data privacy, governance, and responsible AI compliance.Collaborate with product managers, data engineers, and development teams to translate business requirements into technical solutions.Required Qualifications8+ years of experience in software architecture, software engineering, ML engineering, or platform engineering.2+ years of hands‑on experience with AI/ML and Generative AI technologies.Strong programming skills in Python, Java, or similar languages.Expertise in LLMs, prompt engineering, RAG, embeddings, and Agentic AI frameworks.Experience designing enterprise-grade AI architectures and integrating AI into production applications.Strong experience with GCP and cloud‑native application development.Knowledge of vector databases, data pipelines, document processing, and knowledge management.Experience with Kubernetes, Docker, CI/CD, and MLOps practices.Understanding of AI security, guardrails, responsible AI, and enterprise governance.Preferred SkillsExperience with foundation models such as GPT, Claude, or LLaMA.Knowledge of multi‑agent systems, workflow orchestration, and knowledge graphs.Experience with Vertex AI, Big Query, and other GCP services.Familiarity with model evaluation, inference optimization, monitoring, and cost management.Experience with GDPR, data privacy, and regulated enterprise environments.Knowledge of A/B testing, feature flags, and AI product lifecycle management.