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Ai strategist / decisioning expert - aws and gcp (day rate highly negotiable - top rates) hybrid/remote working - london based

Ashton-under-Lyne
Superstars
Posted: 23h ago
Offer description

AI Strategist / Decisioning Expert - AWS and GCP London based Experience: Snr Role (10 years) 2 days Hybrid Working (onsite) / 3 days Remote Working Day Rate: Highly negotiable (Top Rates) My client, an innovative accelerator company specializing in digital transformation, working with a diverse range of clients is looking for a strong AI Strategist / Decisioning Expert with 10 years proven industry experience. The company mission is to drive growth and success for businesses through cutting-edge technology solutions. As they continue to expand, they are seeking an AI Strategist / Decisioning expert to join their dynamic team. Business Translate commercial goals and product catalogue strategy into executable decision logic within the NBA ecosystem. Advise on which KPIs to prioritise to improve the business outcomes of the NBA ecosystem. Mastery in data analytics and visualisation to extract the relevant signals and pattern for better decision-making and prioritisation for faster time-to-market offers. Must be able to work alongside Commercial teams (e.g. base management, pricing) and Product Tribes (e.g. Home, Mobile, TV). Proactively streamline requirement processes and influence the refinement of business activities themselves, beyond execution. Operate as embedded partner within agile squads and tribes for continuous commercial value delivery. Must be capable of challenging the business and drive best practices for better business outcomes. Tech Kotlin : Primary programming language for core NBA applications PostgreSQL (GCP & AWS RDS) : For application configuration and schema management DynamoDB (AWS) : NoSQL data store for high-throughput eligibility and state data Commercial NBA App (containerised microservice in ECS/GKE): Hosts decisioning logic NBA Orchestrator : Coordinates inbound/outbound flows and manages API calls across Pega, Vlocity, and external systems Machine Learning Models via Vertex AI (GCP) AWS Glue Lambda Step Functions : Batch ETL workflows Kafka (Confluent Cloud) : Real-time feature streams ingestion Kinesis Streams Firehose : Traceability and telemetry routing Cloud Storage (S3, GCP buckets) : Configuration, logs, traceability data Envoy Proxy ALB WAF : TLS termination, authentication, traffic routing CloudWatch / Dynatrace : Observability and alerting Terraform GitLab CI/CD : Infrastructure as Code and deployment pipelines Custom UI for simulations/experiments (planned to support with GenAI features in the future) for business configuration, testing, and release governance

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