Senior Cloud Engineer

Overview

Senior hands-on Platform Engineer on the Cloud track, building core AWS infrastructure for Amtech's account-per-customer Encore ERP hosting and multi-tenant LabelTraxx SaaS, and setting the technical standard for the India cloud engineering pod.

What you'll do

• Design and implement scalable, secure AWS infrastructure across Amtech's multi-account organizations, including the account-per-customer Encore hosting model.
• Author and maintain reusable Terraform modules and golden-path IaC patterns that other engineers build on.
• Design DNS, certificate, and network architecture for customer-facing environments (Route 53 delegation, ACM, VPC design).
• Contribute to landing zone evolution, account vending, and multi-environment promotion patterns.
• Build and harden CI/CD pipelines in GitHub Actions for infrastructure and application delivery.
• Operate and optimize containerized and serverless workloads (ECS Fargate, EKS, Lambda) and RDS PostgreSQL at production scale.
• Instrument the platform with the OpenTelemetry-based observability stack (OpenObserve, CloudWatch) and integrate with PagerDuty.
• Own incident response and root cause analysis for cloud infrastructure in your domain, meeting SLA and SLO targets.
• Drive FinOps outcomes: tagging enforcement, right-sizing, Savings Plans coverage, and cost anomaly follow-up.
• Implement cloud security best practices: IAM boundary design, secrets management, network segmentation, and encryption standards.
• Partner with Information Security to enforce SOC 2 and ISO 27001 controls and produce audit evidence through automation.
• Integrate vulnerability scanning, patching, and policy checks into pipelines (shift-left security).
• Uphold Amtech's data governance rules for customer data in all cloud environments.
• Design validation gates for AI-assisted infrastructure changes: what AI may touch, required review depth by blast radius, and rollback and audit trails.
• Establish reusable AI patterns (prompt and context libraries, standard workflows) adopted across the pod, and mentor engineers in safe, high-leverage usage.
• Measure AI productivity impact against baselines; enforce data classification policy in all AI-assisted work.
• Partner with product development teams to enable efficient, self-service deployment models.
• Mentor earlier-career platform engineers in IaC, observability, and secure delivery practices.
• Coordinate daily with U.S. peers and leadership to maintain global consistency across time zones.
• Contribute to architectural reviews, migration planning, and platform standards.

What you'll need

• 7+ years of hands-on experience in cloud, platform, or DevOps engineering, with substantial AWS depth.
• Expert working knowledge of AWS services (EC2, ECS/EKS, S3, RDS, IAM, Lambda, VPC, Route 53) in multi-account environments.
• Strong Terraform expertise, including designing reusable modules consumed by other teams.
• Proven software engineering ability in Python (or similar) applied to platform automation.
• Experience with GitHub Actions or equivalent CI/CD, including secure pipeline design.
• Experience designing observability with OpenTelemetry or equivalent, and operating under SLOs.
• Strong grasp of networking, DNS, TLS, and cloud security architecture.
• Track record of effective collaboration in distributed global teams.
• Track record of team-level AI leverage: designed validation gates for AI-assisted changes and reusable patterns others adopted.
• Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent demonstrated skills.

Nice to have

• AWS Certified DevOps Engineer Professional, Solutions Architect Professional, CKA, or Terraform Associate.
• Experience with account-per-customer or multi-tenant SaaS hosting models, or ERP-class workload migration (lift-and-shift and re-platform).
• Experience with AWS Control Tower, landing zones, and account vending automation.
• FinOps practice experience (tagging governance, Savings Plans strategy, cost allocation).
• Experience operating AI/LLM workloads or building agentic automation under governance controls.

Details

• Location: Bangalore, India.
• Works daily with U.S.-based peers and leadership across time zones.