Join an award-winning B2B consultancy at the forefront of enterprise AI, building and owning the cloud-native platform infrastructure that powers production-grade conversational and generative AI products at scale.The roleThis is a platform and infrastructure engineering role - not a data science or ML engineering position. You''ll own the runtime, infrastructure, and operational layers that RAG pipelines, LLM orchestration, vector search, and evaluation workflows run on, across AWS and Databricks. The focus is on building scalable, observable, secure, and cost-efficient platform infrastructure that enables AI engineering teams to ship and operate AI products reliably in production.What you''ll doDesign, build, and operate cloud-native AI platform infrastructure across AWS (Lambda, API Gateway, DynamoDB, S3, CloudWatch) and DatabricksDeploy and operate containerised services on Kubernetes using Terraform for infrastructure-as-codeOwn and scale vector search infrastructure (OpenSearch, Algolia, AWS Bedrock Knowledge Bases) and embedding pipelinesBuild and maintain CI/CD pipelines for inference services, retrievers, ingestion workflows, and RAG componentsImplement observability across AI workloads using CloudWatch, MLflow, and OpenTelemetry - covering latency, throughput, cost, and system healthApply secure-by-design principles including IAM, encryption, network controls, and audit loggingWork closely with AI engineers to translate prototypes and proof-of-concepts into ..... full job details .....