Senior Cloud & AI Infrastructure Engineer (AWS)

We are hiring for one of our Client/Startup
Only immediate Joiners please
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
-7+ 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)

Work arrangement
No