AI Ops / ML Ops Architect

AI Ops Roles – Job Descriptions  Offshore Solution Architect – AI Ops & Data Platform 

Must Have (Technical) - 10+ years in solution architecture, preferably in AI/DataOps-heavy environments - Strong experience in AWS Glue, Athena, S3, Lambda, CloudWatch - Experience architecting systems using Amazon Bedrock (Agents, Knowledge Base) or SageMaker pipelines - Deep understanding of ETL pipeline orchestration and log telemetry (Airflow, Glue Workflows, Step Functions) - Working knowledge of CI/CD (CodePipeline, CodeBuild, ECR) Good to Have (Technical) - Familiarity with observability tooling (Datadog, X-Ray, Prometheus) - Prior exposure to LangChain or RAG workflows - Terraform/CloudFormation for IaC - Awareness of CBA toolsets like Omnia, Greenfield, Obstack Soft Skills - Strong client-facing communication and documentation skills - Ability to negotiate solution tradeoffs and handle ambiguity - Confident in driving architecture workshops with enterprise stakeholders Project Skills - Translate requirements into architecture and sprint-level workplans - Experience delivering in Agile or DevOps-driven programs - Comfortable working in staff augmentation or client-embedded model Key Responsibilities - Architect and own the delivery of the AI Ops RCA solution end-to-end - Collaborate with client (Tom, Jason) to validate use cases, KPIs, and constraints - Ensure integration of AWS-native tools with client observability, ServiceNow, and DataOps environments - Guide offshore/onshore team in implementation, testing, and rollout - Own platform documentation and handover artifacts