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Senior AWS Full-Stack Engineer

Remote

Feature Development: work as part of an empowered, cross-functional product team to deliver new features using agile methodologies.
Consult with stakeholders, take ownership of issues and participate in ceremonies.
Take responsibility for the successful deployment of your features into production.

AI Tooling & Agentic Workflow: Lead the practical implementation of AI tools within the development lifecycle.
This includes using an Agentic Approach to share specs with coding agents, inviting criticism, and refining AI-generated source code and documentation.
Develop and deploy agents — and supporting infrastructure — to accelerate the software development lifecycle.

Infrastructure: Work with the existing AWS infrastructure defined in CDK (TypeScript), developing a deep understanding of it and implementing amendments as needs evolve.
Contribute to CI/CD pipelines, deployment strategy (blue/green, canary), and environment promotion.
Support the health of Lambda, DynamoDB, OpenSearch and PostgreSQL (RDS) etc.

Observability: Define and configure the observability stack (CloudWatch metrics, logs, traces, alarms, AI-powered anomaly detection) so problems are detected before they are reported.

Site Reliability Engineering: Drive SRE practice — error budgets, runbooks, post-incident reviews — and ensure production systems are reliable, scalable, and efficient through automation and AI monitoring.
Act on tickets received from second line support, develop tooling to empower second line to handle common classes of failure.
Triage issues, perform root cause analysis, implement fixes and manage them through to production.

CI/CD & Release Engineering: Understand and continuously improve the build, test, and deployment pipelines.
Automate the path from commit to production, including release gates, rollback strategies, and pipeline observability.

Security & Networking: Oversee least-privilege IAM, Cognito, and Secrets Manager configurations alongside VPC, subnet, and Route 53 design.

Qualifications

AWS Mastery: Deep knowledge of Lambda (NodeJS/TypeScript), DynamoDB, EventBridge, SQS, and AppSync, plus the networking primitives (VPC, subnets, IAM, Route 53) that hold them together.

IaC: Extensive experience with Infrastructure-as-Code (AWS CDK), including module design, environment parameterisation, and drift detection.

CI/CD & Containers: Hands-on experience designing CI/CD pipelines (GitHub Actions, CodePipeline, or similar) and working with containerised workloads (Docker, ECS/EKS, or Lambda container images).

Observability & SRE: Practical experience with CloudWatch metrics/logs/traces, alerting, on-call practices, and runbook authoring.

AI Proficiency: Experience with AI-native development and automated PR review phases for compliance and code quality.

Bonus: Experience in TV/Media (MediaConvert, MediaLive). Building agentic tooling, semantic search pipelines, MCP servers etc.

Must Have

AWS Mastery: Deep knowledge of Lambda (NodeJS/TypeScript), DynamoDB, EventBridge, SQS, and AppSync, plus the networking primitives (VPC, subnets, IAM, Route 53) that hold them together.IaC: Extensive experience with Infrastructure-as-Code (AWS CDK), including module design, environment parameterisation, and drift detection.CI/CD Containers: Hands-on experience designing CI/CD pipelines (GitHub Actions, CodePipeline, or similar) and working with containerised workloads (Docker, ECS/EKS, or Lambda container images).Observability SRE: Practical experience with CloudWatch metrics/logs/traces, alerting, on-call practices, and runbook authoring.AI Proficiency: Experience with AI-native development and automated PR review phases for compliance and code quality. Bonus: Experience in TV/Media (MediaConvert, MediaLive). Building agentic tooling, semantic search pipelines, MCP servers etc.AI Strategy: Leading the AI-augmented development lifecycle by managing the interaction between human logic and AI execution.Infrastructure: Mastery of AWS CDK (TypeScript).