Senior Cloud Infrastructure Engineer – Mumbai / Hybrid (3)

Compoundexpress Private Limited; Mumbai; On-site; INR 1,400,000 - 2,500,000; Full time

Job summary

Compoundexpress Private Limited is expanding its core infra engineering team to ensure reliability, security, scalability, and operational efficiency of a regulated fintech platform. You will own production systems across AWS, networking, databases, CI/CD, observability, and security, with end-to-end ownership and automation to replace manual ops.

Role emphasizes hands-on production engineering, multi-account AWS design, Terraform-based IaC, and strong incident analysis to drive reliability and

Qualifications

• 8+ years in DevOps, SRE, Cloud Infra or Platform Engineering with production accountability.
• Deep AWS experience across VPC, multi-AZ, networking, compute, storage, and databases.
• Strong Terraform expertise including modules, remote state, and lifecycle management.
• Container fundamentals with Docker and production orchestration (ECS/Kubernetes).
• Strong Linux, Bash and Python automation for reliable ops and tooling.
• Solid CI/CD design, deployment strategies, and release automation.
• Observability across logs/metrics/traces; incident investigations and RCA.
• Identity, secrets, encryption, least privilege, and cloud security basics.

Responsibilities

• Architect and operate multi-account AWS environments using Organizations and IAM.
• Design and optimize production workloads across ECS, EC2, RDS PostgreSQL, and S3.
• Build and govern IaC with Terraform/Terragrunt and reusable modules.
• Own GitLab CI/CD pipelines, deployment strategies, and rollback mechanisms.
• Build reliable container platforms with Docker optimization and ECS operations.
• Lead troubleshooting of distributed-system failures across infra, network, app, container, and DB layers.
• Operate RDS PostgreSQL including tuning, VACUUM/ANALYZE, backups, replication, and capacity planning.
• Develop observability with dashboards, alerts, and SLOs; manage secrets and encryption.
• Design disaster recovery strategies across regions; perform DR exercises.
• Lead incident investigations, root-cause analysis and preventive actions.

Skills

DevOps mindset

Problem solving

Independent investigation

Tools

Terraform/Terragrunt

AWS (VPC, IAM, EC2, ECS, RDS)

CI/CD (GitLab)

Docker / containerization

Kubernetes

Python / Bash automation

Observability (OpenTelemetry, Grafana, CloudWatch)

Networking & security

Terraform state management

Job description

Positions: 3

What Is This Role About?

We are expanding our core infrastructure engineering team responsible for the reliability, security, scalability, and operational efficiency of a regulated fintech platform. This is a hands‑on production engineering role. You will work across AWS infrastructure, networking, databases, CI/CD, observability, security, disaster recovery, and automation. We are looking for engineers who can independently investigate complex problems, make sound technical decisions, automate repetitive work, and take end-to-end ownership of production systems. This is not a ticket‑driven DevOps role.

What You'll Own

• Architect and operate multi‑account AWS environments using AWS Organizations, Control Tower, IAM, and IAM Identity Center.
• Design, build, operate, and optimize production workloads across ECS, EC2, ALB/NLB, RDS PostgreSQL, Lambda, S3, EFS, and related AWS services.
• Design and troubleshoot AWS networking including VPCs, subnets, route tables, NAT, Transit Gateway, security groups, load balancers, DNS, VPC endpoints, and hybrid connectivity.
• Build and govern Infrastructure as Code using Terraform/Terragrunt, including reusable modules, standards, state management, and infrastructure lifecycle management.
• Own and improve GitLab CI/CD pipelines, runners, deployment strategies, environment promotion, rollback mechanisms, and release automation.
• Build reliable container platforms with strong understanding of Docker image optimization, runtime behaviour, resource allocation, scaling, and ECS operations.
• Lead troubleshooting of complex distributed‑system failures across infrastructure, network, application, container, and database layers.
• Operate Amazon RDS for PostgreSQL, including performance analysis, query tuning, indexing, VACUUM/ANALYZE, backup/recovery, replication, capacity planning, and operational troubleshooting.
• Build observability across logs, metrics, traces, dashboards, alerts, and SLOs using platforms such as CloudWatch, Grafana, and OpenTelemetry‑compatible tooling.
• Manage secrets, IAM boundaries, encryption, certificates, KMS, and security controls across infrastructure and applications.
• Design and validate disaster recovery strategies across AWS regions and accounts, including recovery automation and periodic DR exercises.
• Lead production incident investigation, root‑cause analysis, corrective actions, and prevention of recurring failures.
• Identify and drive AWS cost optimization across compute, databases, storage, networking, logging, and data transfer without compromising reliability.
• Participate in architecture reviews, capacity planning, security reviews, production‑readiness reviews, and infrastructure design decisions.
• Replace manual operational processes with reliable automation using Python, Bash, APIs, Infrastructure as Code, and modern DevOps tooling.
• Work closely with developers, QA, security, and operations teams to improve software delivery and production reliability.
• Mentor engineers, review infrastructure changes, and help establish engineering standards across the team.

Must-Have Skills

Candidates are expected to bring strong hands‑on experience in the following areas from day one:

• 8+ years of hands‑on experience in DevOps, SRE, Cloud Infrastructure, or Platform Engineering roles with direct production accountability.
• Deep AWS experience, including VPC architecture, multi‑AZ design, networking, IAM, compute, storage, databases, scaling, and production troubleshooting.
• Strong AWS networking fundamentals including routing, NAT, Transit Gateway, DNS, load balancing, private connectivity, and network troubleshooting.
• Advanced Terraform expertise, including reusable module design and authoring, remote state management, environment separation, and infrastructure lifecycle management.
• Strong container fundamentals including Docker image optimization, runtime troubleshooting, resource tuning, and production container orchestration.
• Strong Linux fundamentals and hands‑on Bash and/or Python automation.
• Strong understanding of CI/CD architecture and production deployment strategies.
• Deep debugging capability across infrastructure, application, network, container, and database layers.
• Hands‑on observability experience across logs, metrics, dashboards, alerting, and production incident investigation.
• Strong understanding of IAM, secrets management, encryption, least privilege, and cloud security fundamentals.
• Cloudflare, CDN, WAF, or reverse‑proxy experience including routing, caching, TLS/SSL, security policies, and troubleshooting.
• Ability to independently investigate unfamiliar production problems using logs, metrics, traces, system behaviour, documentation, and first principles.

Preferred Skills

• Kubernetes production operations and troubleshooting.
• GitOps and declarative infrastructure/application delivery.
• OpenTelemetry, distributed tracing, and modern observability practices.
• Platform engineering, Internal Developer Platforms, self‑service infrastructure, or developer experience initiatives.
• Apache Airflow or similar workflow orchestration platforms.
• Multi‑region AWS disaster recovery architecture and DR automation.
• Advanced PostgreSQL administration and performance tuning.
• Cloud security and compliance experience in regulated environments.
• SOC 2, ISO 27001, CERT‑In, SEBI, or similar regulatory/compliance exposure.
• IAM federation, SSO, and enterprise identity architecture.
• Infrastructure policy‑as‑code and automated compliance controls.
• Software supply‑chain security, container scanning, secrets scanning, and CI/CD security controls.

AI & Automation Expectations

AI‑assisted engineering will increasingly be part of infrastructure operations. We expect engineers to use it responsibly, not blindly. You should be able to:

• Use AI tools to accelerate investigation, scripting, documentation, automation, and operational analysis.
• Understand and validate AI‑generated code, infrastructure changes, SQL, scripts, and recommendations before using them.
• Never execute AI‑generated production changes without understanding their behaviour and potential blast radius.
• Identify opportunities where repetitive operational work can be safely automated.
• Design automation with appropriate validation, auditability, permissions, rollback, and human controls.
• Treat AI as an engineering accelerator, not a substitute for technical understanding.

How We Expect You to Operate

This is not a checkbox role. We expect engineers to:

• Take ownership of problems from detection through permanent resolution.
• Make technical decisions within their area of responsibility without waiting for step‑by‑step instructions.
• Investigate incidents using evidence rather than assumptions.
• Argue with data, not opinions.
• Understand the systems they operate rather than treating infrastructure as a collection of configuration files.
• Automate repetitive work instead of repeatedly performing manual operations.
• Consider reliability, security, performance, operability, and cost when making infrastructure decisions.
• Understand the blast radius before making production changes.
• Challenge existing architecture when there is a technically better approach.
• Document important architectural decisions, operational procedures, and failure scenarios.
• Be comfortable working across boundaries, from VPCs and DNS to CI/CD, containers, databases, observability, and security.
• Leave systems more reliable and easier to operate than they found them.

This Role Is Not a Fit If You

• Have primarily certification‑based or theoretical AWS knowledge without substantial hands‑on production experience.
• Have mostly operated pre‑built pipelines and infrastructure without understanding how they work underneath.
• Avoid production systems or are uncomfortable taking ownership during incidents.
• Depend on step‑by‑step instructions to investigate unfamiliar technical problems.
• Escalate issues without first investigating logs, metrics, configuration, dependencies, and system behaviour.
• Use AI‑generated solutions without understanding and validating what they do.
• Prefer narrowly defined responsibilities and are uncomfortable troubleshooting across infrastructure layers.
• Treat recurring manual operational work as normal instead of looking for ways to automate it.
• Focus only on making a system work without considering reliability, security, scalability, operability, and cost.