Mid-Level Architect (Observability/Analytics)

As a Software Architect, you will play a crucial role in leading the design and delivery of scalable, cloud-native AI/ML solutions. Your main responsibility will be translating complex business requirements into robust technical architectures that empower Autonomous AI Agents in various enterprise domains. Here is a breakdown of your key responsibilities: - Architect end-to-end AI/ML solutions and establish system design standards for cloud-native microservices and agentic workflows. - Conduct technical design reviews, assess architectural patterns, and provide guidance to engineering teams for creating clean and maintainable implementations. - Drive the development of GenAI solutions by exploring advanced foundation models and seamlessly integrating them into production pipelines. - Take ownership of ensuring the reliability and scalability of containerized services on Kubernetes across different cloud platforms such as AWS, Azure, or GCP. - Create comprehensive architecture documentation, decision records, and runbooks to facilitate team-wide alignment. To excel in this role, you must meet the following requirements and qualifications: - 10+ years of experience in software development and architecture. - Bachelor's degree or higher in Computer Science or a related field. - Proficiency in Python and/or Java. - Knowledge of agentic frameworks such as LangChain, AutoGen, CrewAI, or similar. - Hands-on experience in designing and deploying microservices on cloud platforms like AWS, Azure, or GCP. - Deep understanding of Kubernetes for container orchestration. - Practical experience with AI/ML technologies and GenAI solution development. - Strong Linux/Unix Bash scripting skills. - Excellent written and verbal communication skills to effectively communicate complex architecture concepts to non-technical stakeholders. In addition to the mandatory qualifications, the following skills and experiences would be considered advantageous: - Familiarity with RAG (Retrieval-Augmented Generation), vector databases, or fine-tuning LLMs. - Cloud certifications such as AWS Solutions Architect, Azure Solutions Architect, or GCP Professional Cloud Architect. - Exposure to CI/CD pipelines, DevSecOps practices, and Infrastructure-as-Code tools like Terraform or Pulumi. - Experience with event-driven architectures utilizing tools like Kafka or RabbitMQ. This job offers the opportunity to work on cutting-edge AI/ML solutions within a dynamic and innovative environment. As a Software Architect, you will play a crucial role in leading the design and delivery of scalable, cloud-native AI/ML solutions. Your main responsibility will be translating complex business requirements into robust technical architectures that empower Autonomous AI Agents in various enterprise domains. Here is a breakdown of your key responsibilities: - Architect end-to-end AI/ML solutions and establish system design standards for cloud-native microservices and agentic workflows. - Conduct technical design reviews, assess architectural patterns, and provide guidance to engineering teams for creating clean and maintainable implementations. - Drive the development of GenAI solutions by exploring advanced foundation models and seamlessly integrating them into production pipelines. - Take ownership of ensuring the reliability and scalability of containerized services on Kubernetes across different cloud platforms such as AWS, Azure, or GCP. - Create comprehensive architecture documentation, decision records, and runbooks to facilitate team-wide alignment. To excel in this role, you must meet the following requirements and qualifications: - 10+ years of experience in software development and architecture. - Bachelor's degree or higher in Computer Science or a related field. - Proficiency in Python and/or Java. - Knowledge of agentic frameworks such as LangChain, AutoGen, CrewAI, or similar. - Hands-on experience in designing and deploying microservices on cloud platforms like AWS, Azure, or GCP. - Deep understanding of Kubernetes for container orchestration. - Practical experience with AI/ML technologies and GenAI solution development. - Strong Linux/Unix Bash scripting skills. - Excellent written and verbal communication skills to effectively communicate complex architecture concepts to non-technical stakeholders. In addition to the mandatory qualifications, the following skills and experiences would be considered advantageous: - Familiarity with RAG (Retrieval-Augmented Generation), vector databases, or fine-tuning LLMs. - Cloud certifications such as AWS Solutions Architect, Azure Solutions Architect, or GCP Professional Cloud Architect. - Exposure to CI/CD pipelines, DevSecOps practices, and Infrastructure-as-Code tools like Terraform or Pulumi. - Experience with event-driven architectures utilizing tools like Kafka or RabbitMQ. This job offers the opportunity to work on cutting-edge AI/ML solutions within a dynamic and innovative environment.