Job Summary

We are seeking a Senior/Lead Platform Engineer to support our AI, Data Engineering, and Data Platform initiatives. This role will be responsible for designing, implementing, and maintaining cloud infrastructure, deployment automation, platform reliability, security controls, and operational excellence across multiple products and environments.

The ideal candidate will have strong AWS experience, infrastructure-as-code expertise, Terraform GitHub expertise, CI/CD knowledge, and a passion for improving platform reliability, security, and operational maturity. Knowledge in Azure and Google Cloud Platform (GCP) will be considered an advantage.

Key Responsibilities

- Lead the design, architecture, implementation, and evolution of secure, scalable, highly available cloud platforms on AWS that support enterprise applications, AI, and data platform initiatives.
- Define and drive the platform engineering roadmap, standards, and best practices for cloud infrastructure, automation, reliability, and operational excellence.
- Architect and maintain Infrastructure as Code (IaC) solutions using Terraform to ensure consistent, repeatable, and scalable infrastructure provisioning.
- Lead the design, operation, and optimization of Kubernetes (Amazon EKS) platforms and containerized workloads, ensuring high availability, security, and performance.
- Drive the adoption of DevOps and Platform Engineering practices by designing and improving CI/CD pipelines, GitHub Actions workflows, deployment automation, and developer self-service capabilities.
- Establish and continuously improve platform reliability through observability, monitoring, logging, alerting, incident management, capacity planning, and performance optimization.
- Provide technical leadership for AWS platform services, including VPC, IAM, EC2, EKS, ECS, Lambda, RDS, S3, Route 53, Secrets Manager, CloudWatch, and other cloud-native technologies.
- Partner with application, AI, data engineering, and security teams to design scalable platform solutions and enable the deployment, orchestration, monitoring, and operational support of AI-powered applications, LLM services, and agentic workflows while improving developer productivity, deployment consistency, and operational efficiency.
- Lead the implementation of cloud security best practices, including identity and access management, secrets management, infrastructure hardening, vulnerability remediation, governance, and compliance controls.




- Define and oversee disaster recovery, business continuity, backup strategies, and platform resiliency to meet organizational recovery objectives.
- Lead infrastructure modernization, cloud migration, platform standardization, and technology adoption initiatives across multiple environments.
- Drive cloud governance, resource optimization, and FinOps initiatives to improve operational efficiency, scalability, and cost management.
- Establish platform standards, operational procedures, technical documentation, and architectural guidelines to ensure consistency and knowledge sharing across engineering teams.
- Provide technical leadership during production incidents, lead root cause analysis, and implement preventive measures to improve platform stability and operational maturity.
- Mentor and coach Platform Engineers, foster engineering excellence, conduct design and code reviews, and champion a culture of automation, continuous improvement, collaboration, and operational ownership.
- Evaluate emerging cloud technologies, tools, and architectural patterns, providing technical recommendations that align with the organization's long-term platform strategy.

Required Qualifications
- 8+ years of experience in Cloud Engineering, DevOps, Platform Engineering, Site Reliability Engineering (SRE), or a related infrastructure engineering role.
- Strong hands-on experience designing, implementing, and operating solutions on Amazon Web Services (AWS).
- Working knowledge of Microsoft Azure and Google Cloud Platform (GCP) is desirable.
- Proven ability to independently drive technical initiatives from concept to delivery with minimal supervision and ambiguous requirements.
- Robust experience with Infrastructure as Code (IaC) using Terraform.
- Hands-on experience managing Kubernetes environments, with Amazon EKS preferred.
- Experience with containerization technologies, including Docker, and cloud-native application deployment.
- Strong experience designing, implementing, and maintaining CI/CD pipelines using modern DevOps tools.




- Proficiency in scripting and automation using Python, Bash, or similar programming languages.
- Experience with Git, GitHub, GitHub Actions, and source control best practices.
- Solid understanding of cloud networking concepts, including VPCs, IAM, DNS, load balancing, security groups, routing, and cloud architecture principles.
- Strong troubleshooting and root cause analysis skills for complex infrastructure, networking, Kubernetes, and application issues.
- Experience implementing observability and monitoring solutions for cloud-native environments.
- Excellent written and verbal communication skills, with the ability to collaborate effectively across cross-functional teams.
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.

Preferred Qualifications
- Experience supporting AI/ML platforms, LLM-based applications, Agentic AI solutions, Model Context Protocol (MCP) integrations, data engineering pipelines, or modern data platform architectures.
- Experience with GitOps practices and tools such as Argo CD or Flux.
- Hands-on experience with observability and monitoring platforms such as Prometheus, Grafana, OpenTelemetry, CloudWatch, Datadog, or Splunk.
- Experience implementing DevSecOps practices, including vulnerability management, policy-as-code, secrets management, and compliance automation.
- Knowledge of service mesh technologies (e.g., Istio or Linkerd) and Kubernetes networking.
- Experience with serverless technologies and event-driven architectures.
- Familiarity with messaging and streaming platforms such as Apache Kafka, Amazon MSK, or RabbitMQ.
- Experience designing and implementing disaster recovery, backup, and high-availability solutions.
- Knowledge of cost optimization and FinOps best practices for cloud infrastructure.
- Experience managing multi-account and multi-region cloud environments.
- Familiarity with data lake, data warehouse, or analytics platforms such as Trino, Iceberg, Spark, Snowflake, or Amazon Redshift.
- Experience contributing to platform engineering initiatives that improve developer experience through self-service infrastructure and automation.
- Experience mentoring engineers, conducting technical reviews, and promoting engineering best practices.
- AWS Professional, Kubernetes (CKA/CKAD), Terraform, or other relevant cloud certifications are a plus.

📌 Lead Platform Engineer (Gurugram)
🏢 Su0026P Global Market Intelligence
📍 Gurugram