Senior AI Ops Architect

Job description

We are seeking a highly experienced **Senior AI Ops Architect** with exceptional expertise in Gen-AI-enabled Cloud Engineering, Observability, Operational Intelligence, and AI-driven automation. The ideal candidate will bring 10+ years of enterprise-level architecture experience, with a focus on building innovative Gen-AI-enabled platforms, data-driven automation frameworks, and enterprise-grade AIOps solutions to advance operational efficiency. **Responsibilities** - Design and deliver scalable Gen-AI-powered AIOps solutions for large enterprise platforms to improve MTTR, achieve automated incident resolution, and drive operational excellence - Architect and implement Gen-AI & LLM Engineering solutions using tools such as Amazon Bedrock, Azure OpenAI, Vertex AI, Anthropic, and LangChain - Develop and optimize MLOps pipelines and model deployment workflows leveraging SageMaker, Azure ML, clustering, topic modeling, and anomaly detection techniques - Implement RAG, Vector DBs, and advanced semantic search across platforms using PGVector, Elasticsearch, and Bedrock Knowledge Sources - Create and automate solutions for Cloud Platforms and Infrastructure with AWS, Azure, GCP, Terraform, CloudFormation, and Helm, alongside Python and Shell Scripting - Lead Kubernetes-based container orchestration and DevSecOps initiatives, including CI/CD pipelines, Istio, and KEDA deployment strategies - Design and integrate serverless and cloud-native architectures using API Gateway, Lambda, Step Functions, DynamoDB, S3, and Kinesis - Implement end-to-end Observability solutions using DataDog, OpenTelemetry, Dynatrace, New Relic, Splunk, Moogsoft, and BigPanda - Ensure seamless ITSM and ServiceNow integration for AI-driven operations and automation - Work with ITSM tools like ServiceNow, Jira Service Management, and Manage Engine to streamline incident management workflows - Provide thought leadership in AIOps, automation, and AI-powered operational intelligence to leadership and engineering teams **Requirements** - 19+ years of overall IT experience - 10+ years of professional experience in Enterprise Cloud, Infrastructure Engineering, SRE, Automation, and Architecture roles - Proven track record of delivering Gen-AI-powered AIOps solutions in production environments, driving efficiencies like MTTR improvement and operational automation - Expertise in Gen-AI and LLM Engineering tools such as Amazon Bedrock, Azure OpenAI, Vertex AI, Anthropic, LangChain, and Bedrock Agents - Proficiency in RAG, Vector Databases, and semantic search solutions like PGVector, Elasticsearch, and Bedrock Knowledge Sources - Background in MLOps, model development, and machine learning techniques using SageMaker, Azure ML, clustering, topic modeling, and anomaly detection - Skills in cloud engineering and automation technologies, including AWS, Azure, GCP, Terraform, CloudFormation, Helm, Python, and Shell Scripting - Capability to design and operate Kubernetes-based infrastructure, CI/CD pipelines, security automation, Istio, and KEDA - Familiarity with serverless computing and cloud-native tools like API Gateway, Lambda, Step Functions, DynamoDB, S3, and Kinesis - Knowledge of Observability platforms such as DataDog, OpenTelemetry, Dynatrace, New Relic, Splunk, Moogsoft, and BigPanda - Understanding of ITSM platforms, including ServiceNow, Jira Service Management, and Manage Engine - Showcase of AI and Machine Learning expertise in areas like anomaly detection, GenAI implementation, and agentic AI solutions - Ability to communicate effectively in both written and spoken English (B2 level or higher) **Nice to have** - Experience leading AIOps/Cloud Practices or platform engineering organizations - Certifications in AWS ML, Cloud Architecture, or AI Leadership