SelectorAI SME

SelectorAI 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 clients 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 clients 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