Cloud & AI Infrastructure Engineer (AWS)

We are hiring for one of our Client/Startup

The Role

You will own the cloud infrastructure that powers a production SaaS platform serving financial

institutions. This is not a passive keep-the-lights-on role — you will architect scaling strategies,

optimise costs, harden security, and build the infrastructure backbone for AI workloads. As an

early hire at a high-growth startup, you will also contribute to application development across

the stack when needed.

Primary Responsibilities

- Cloud Infrastructure Ownership — Manage and evolve the AWS production

environment: compute, networking, storage, databases, caching, and security services

-Scaling & Performance — Design and implement auto-scaling strategies, diagnose

production bottlenecks, and ensure the platform handles growing client workloads

reliably

-Infrastructure as Code — Own and extend the Terraform codebase for repeatable,

auditable infrastructure deployments

-AI/ML Infrastructure — Support and scale AI workloads including LLM service

deployments, model inference pipelines, and vector storage

-CI/CD & Deployment — Maintain and improve automated build, test, and deployment

pipelines across backend and frontend services

-Observability & Incident Response — Build and maintain monitoring, alerting, and

distributed tracing; lead incident diagnosis and resolution

-Security & Compliance — Uphold security best practices for a FinTech platform,

including encryption, access controls, WAF management, and compliance readiness

(SOC2, AWS FTR)

-Cost Optimisation — Monitor cloud spend, right-size resources, and implement

cost-saving strategies as the platform scales.

Secondary Responsibilities

-Contribute to backend and/or frontend application development as needed - -

-Collaborate with business and operations teams on client onboarding infrastructure

-Evaluate and integrate new AWS services or third-party tools that benefit the platform.

What We're Looking For

Must Have

-3+ years hands-on experience with AWS in a production environment

-Strong experience with containerised workloads (ECS/Fargate or EKS, Docker, ECR)

-Proficiency in Infrastructure as Code (Terraform strongly preferred)

-Experience with CI/CD pipelines (GitHub Actions, GitLab CI, or similar)

-Solid understanding of networking (VPC, subnets, security groups, load balancers,

DNS)

-Experience with managed databases (RDS PostgreSQL, ElastiCache/Redis)

-Familiarity with monitoring and observability tools (CloudWatch, X-Ray, Grafana, or

similar)

-Working knowledge of Linux, scripting (Bash/Python), and troubleshooting production

issues

-Understanding of security fundamentals: IAM, encryption at rest/in transit, secrets

management

Great to Have

-Experience scaling AI/ML workloads in production (model serving, GPU instances,

managed AI services like Bedrock/SageMaker)

-Backend development experience with Python (Django/FastAPI)

-Frontend development experience (React/Next.js)

-Experience with asynchronous task processing (Celery, SQS, or similar)

- Exposure to FinTech or regulated environments (SOC2, FTR, compliance

frameworks)

-Experience with S3 lifecycle management, CloudTrail, GuardDuty, or Security Hub

-Familiarity with serverless patterns (Lambda, Amplify)