We are looking for a highly experienced and certified AI Architect to lead the design and execution of AI and GenAIbased systems across our enterprise The ideal candidate will work closely with AI Developers and MCP Developers to define scalable secure and modular architectures that support autonomous agents multiagent orchestration and intelligent automation use cases
This role requires a blend of expertise in cloud infrastructure microservices AIML pipeline development enterprise systems
Key Responsibilities
- Architect and oversee the implementation of AI and GenAIbased solutions across multiple environments
- Collaborate with AI Developers and MCP Developers to design reusable multiagent systems and control planes
- Define scalable and modular microservices architectures using containerized services
- Design and implement authentication and centralized logging for AI microservices and pipelines
- Lead the development of endtoend ML and AI pipelines for data preprocessing training deployment and monitoring
- Govern integration with enterprise systems such as ITSM monitoring security and IAM platforms
- Ensure security observability and compliance in AI solution architecture
- Evaluate and integrate LLM providers OpenAI Azure OpenAI Bedrock etc and GenAI tooling
- Engage with customers to understand their business needs and translate them into AIML solutions
- Present architectural strategies roadmaps and demos to internal and external stakeholders
Required Skills
- AWS or Azure Certification Solutions Architect AIML Speciality preferred
- Proven experience in designing and deploying microservicesbased architectures
- Strong knowledge of authentication mechanisms OAuth JWT API Keys and centralized logging ELK OpenTelemetry etc
- Handson experience with AIML and GenAI technologies frameworks LangChain LangGraph CrewAI and vector DBs
- Experience developing and orchestrating ML workflows and AI pipelines eg Kubeflow MLflow Airflow
- Strong understanding of cloudnative deployments using Docker and Kubernetes
- Familiarity with enterprise infrastructure application monitoring and system integrations
- Excellent communication and interpersonal skills to handle technical and business discussions with customers
Positive to Have
- Experience with RAG architecture finetuning models or serving LLMs
- Background in MLOps and AI governance
- Exposure to ServiceNow SharePoint or Enterprise Observability Platforms
- Experience guiding AI product strategy and roadmap in collaboration with stakeholders