Job Description

AI Strategist / Decisioning Expert - AWS and GCP

Daily Rate - Top High End

London based

Experience: Snr Role (10+ years)

2 days Hybrid Working (onsite) / 3 days Remote Working

Day Rate: Highly negotiable (Top Rates)

Key Essential Skills:

NBA, POSTGREAY, AWS, Kinesis, GCP ,Kafka, Streaming Analytics and Kotlin, Vertex AI, S3 and Terraform.

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 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