Senior Data Engineer

· Architect scalable, resilient, and cost-efficient AI solutions using AWS serverless and managed services.

· Build orchestration workflows using AWS Lambda, Step Functions, EventBridge, API Gateway, and container services where required.

· Implement AI observability, request tracing, usage metrics, logging, alerting, and operational dashboards using CloudWatch and AgentCore capabilities.

· Establish CI/CD pipelines, Infrastructure as Code, automated testing, prompt versioning, and environment promotion practices.

· Optimise model selection, inference configuration, latency, throughput, token usage, and overall platform cost.

· Implement Amazon Bedrock Guardrails and approved runtime controls for prompts and model responses.

· Address risks such as prompt injection, data leakage, hallucinations, unsafe outputs, excessive agency, and unauthorised tool usage.

· Apply IAM least privilege, encryption, secrets management, network security, audit logging, and data protection standards.

· Build evaluation frameworks to measure accuracy, groundedness, relevance, safety, latency, reliability, and cost.

· Ensure AI solutions comply with enterprise architecture, security, privacy, risk, and responsible AI requirements.

· Define AWS AI engineering standards, reference architectures, reusable patterns, and development best practices.

· Lead solution design, architecture reviews, code reviews, testing reviews, and production readiness assessments.

· Mentor AI engineers and software engineers in Bedrock, AgentCore, RAG, agentic AI, and cloud-native development.

· Partner with product owners, data engineers, security teams, architects, and business stakeholders to identify and prioritise high-value AI opportunities.

· Translate business needs into scalable AI products with clear success measures and measurable business outcomes.