Selector AI SME/Selector AI Lead/Selector AI Consultant-Remote

• Client prefers someone onsite 3 days a week but could be flexible for remote if they exhaust local options- Selector AI SME will be creating. proof of concept. If they are a BigPand SME and has some decent experience with Selector AI would be considered. Selector AI SME Overview The Selector AI Engineer will serve as a technical subject-matter expert (SME) responsible for deploying, integrating, and supporting the Selector AI platform within the client's lab and infrastructure environments. This role is hands-on and highly technical, involving configuration, data integration, performance monitoring, documentation, and collaboration with client engineering teams to ensure the platform meets defined use cases and acceptance criteria. Key Responsibilities Assist the client with configuration, deployment, and integration of the Selector AI platform within the client's lab environment, providing hands-on, keyboard-level implementation support Collaborate with client engineers to develop, expand, and refine product use cases, including defining and validating acceptance criteria Support client engineers in monitoring the Kubernetes (K8s/MKS) cluster and underlying infrastructure that supports the Selector platform Identify, define, and help measure performance and operational KPIs Create and maintain technical documentation in collaboration with client engineers, including: Platform usage within the client environment Operational runbooks and internal support procedures Assist with the setup, configuration, and validation of data feeds into the Selector platform Participate in data validation activities to ensure the platform is functioning as expected and delivering accurate, reliable insights Act as a Selector AI subject-matter expert, providing expert-level recommendations to the client on: Platform setup and configuration Integration patterns Metrics, monitoring, and performance optimization Ongoing operational support and best practices Required Skills & Experience Hands-on experience deploying and supporting Selector AI or similar AIOps / observability platforms Strong background in Kubernetes (K8s) and containerized infrastructure monitoring Experience with data ingestion pipelines, data validation, and system integrations Familiarity with performance metrics, KPIs, and observability tooling Ability to collaborate closely with client engineering teams in a lab or pre-production environment Strong documentation skills with the ability to translate technical processes into clear operational guides Preferred Qualifications Experience supporting enterprise or financial-services environments Background in AIOps, monitoring, or observability platforms (e.g., Selector, Datadog, Dynatrace, New Relic, Prometheus) Experience working in proof-of-concept (PoC) or lab environments prior to production rollout Apply tot his job