Aafaq Rana
Verified Expert in Engineering
DevOps and AI Engineer and Developer
Lahore, Pakistan
Toptal member since August 6, 2026
Aafaq is a senior DevOps and AI engineer who specializes in agentic DevOps and large-scale cloud platforms. Over 6 years, he has led legacy modernization programs, built autonomous AI agents for infrastructure operations, and engineered Kubernetes platforms at Netsol Technologies. His expertise spans AWS, Azure, GCP, and Kubernetes, where Aafaq cut build-and-ship time by 50% and improved delivery throughput by 30%.
Portfolio
Experience
- Amazon Web Services (AWS) - 6 years
- Azure DevOps - 6 years
- Kubernetes - 6 years
- DevOps - 6 years
- Docker - 6 years
- Python - 6 years
- Azure - 4 years
- Artificial Intelligence (AI) - 2 years
Work Experience
Senior DevOps Engineer
Netsol
- Managed multiple concurrent DevOps projects and cross-functional engineering teams as part of the platform management group, owning delivery planning, technical direction, stakeholder coordination, and the mentoring of DevOps and SRE engineers.
- Supervised the E2E modernization of legacy products by migrating source control from SVN to Azure DevOps Repos (git-svn) and replatforming CI/CD from legacy Jenkins to standardized Azure DevOps YAML pipelines, cutting build and ship time by 50.
- Applied agentic AI to automatically document legacy and internal codebases and ingest them into a centralized RAG knowledge base on ChromaDB, accelerating onboarding and incident response to reduce MTTR and improve DORA metrics.
- Engineered a Kubernetes AI agent on the Kubernetes MCP Server to autonomously monitor cluster health, detect anomalies, and predict failures before production impact, driving proactive LangGraph-based remediation and reducing unplanned outages.
- Converted traditional observability pipelines into autonomous agentic workflows with LangChain and LangGraph, enabling AI-driven incident triage, automated root-cause analysis, and self-healing across Prometheus, Grafana, and the EFK Stack.
- Designed scalable cloud-native and hybrid infrastructure with Terraform and AWS CDK across AWS, Azure, GCP, and OCI, with secure networking, IAM, encryption, and resilient multi-cloud architectures.
- Built and managed on-premise K3S clusters with Harbor, Longhorn, and custom operators, applying RBAC, ingress, workload isolation, and cluster hardening for reliability and resilience.
- Engineered multi-cloud CI/CD using Azure DevOps, GitHub Actions, and Google Cloud Build with Argo CD across EKS, AKS, GKE, OKE, and K3S, integrating automated testing, Snyk scanning, and Sysdig monitoring aligned with OWASP best practices.
- Embedded IaC validation and policy-as-code (PaC) into CI/CD using Terraform, Checkov, and tfsec to catch misconfigurations, enforce governance, and support compliance via Vanta.
- Built centralized observability with EFK, Prometheus, Grafana, Azure Monitor, and Sysdig for proactive alerting, incident investigation, resilience testing, and chaos engineering.
Infrastructure Benchmark Engineer (IaC)
Vera Platforms
- Authored Terraform and AWS infrastructure benchmark tasks for AI agent training, each designed to fail frontier models at pass@4 against real cloud resources.
- Built Python and boto3 graders that verify the live AWS end state by signing real API calls as different identities, with retries for eventual consistency.
- Automated task setup and teardown: provisioned real AWS resources, seeded applied Terraform state into agent sandboxes, and kept answer keys hidden.
- Diagnosed an evaluation harness setting (a 96k-token ceiling, no real task uses) that made a task look easy; at the default, the same task failed 3 of 4 runs.
- Analyzed agent trajectories to separate genuine model failures from task defects, and wrote fairness rebuttals defending each task to client reviewers.
- Identified a platform bug where inconclusive rollouts dropped unattributed failures from counted rates, protecting the accuracy of task difficulty measurements.
Senior DevOps & LLM Trainer
Turing
- Evaluated large language models (LLMs) on IaC and DevOps tasks using RLHF, preference ranking, and reward modeling by benchmarking outputs with pass@k, HumanEval, and functional-correctness metrics across Terraform, CDK, and cloud automation.
- Designed adversarial multi-step agentic evaluation scenarios for LLM reasoning on Kubernetes, Terraform, and cloud architecture by contributing preference data and rubrics to improve IaC code-generation alignment and safety.
- Built the test automation platform (TAP) with Terraform, CDKTF, AWS CDK, CloudFormation, and Pulumi to provision scalable AWS environments for model training and evaluation with IAM, encryption, and network isolation.
- Delivered cloud environments aligned to the AWS Well-Architected Framework by emphasizing reliability, operational excellence, and cost optimization.
- Performed IaC validation and policy enforcement for Terraform- and CDK-based environments by identifying misconfigurations and validating IAM controls to strengthen governance.
Associate Software Engineer
Devsinc
- Deployed Python FastAPI applications to EC2 via Azure DevOps pipelines with secure automated release processes.
- Used Terraform for IaC deployments across AWS and Azure to enable consistent and reliable infrastructure.
- Built a web-based document processing application in Ruby on Rails that improved processing speed by 20%.
- Deployed front- and back-end applications on AWS with high availability and redundancy across multiple environments.
Project History
Personal Portfolio Site Development and Deployment
http://aafaq-rana.spaceIndustrial LLM Platform
https://github.com/aafaq01/industrial-llm-stackAI Meeting Notetaker
https://fathom-rebuild-five.vercel.appEducation
Bachelor's Degree in Computer Science
School of Electrical Engineering and Computer Sciences - Islamabad, Pakistan
Certifications
AWS Certified Solutions Architect - Associate
Amazon Web Services (AWS)
Skills
Libraries/APIs
REST APIs, Playwright, Node.js, vLLM, Claude API
Tools
Terraform, AWS Cloud Development Kit (CDK), Amazon Elastic Container Service (ECS), GitHub, Observability Tools, Azure Kubernetes Service (AKS), AWS CloudFormation, AWS CloudTrail, AWS IAM, Amazon CloudWatch, Amazon EKS, Amazon Elastic Block Store (EBS), Amazon Elastic Container Registry (ECR), Amazon Virtual Private Cloud (VPC), Kubernetes HorizontalPodAutoscaler (HPA), Sentry, Claude, Logging, GitLab CI/CD, GitLab, Amazon Simple Email Service (SES), PyPI, VMware, ELK (Elastic Stack), GitHub Copilot, Claude Code, Codex, Azure App Service, Azure Application Insights, Azure Network Security Groups, Git, Helm, Azure Monitor, Postman, VPN, Ansible, Amazon Lex, Amazon Connect, OpenTofu, CircleCI, Amazon SageMaker, Microsoft Power BI, Salesforce DX, Kafka Streams, Subversion (SVN), Jenkins, Grafana, EFK Stack, Checkov
Languages
Python, Bash, Bash Script, Bicep, TypeScript, SQL, YAML, Snowflake, Go
Frameworks
Windows PowerShell, AWS Well-Architected Framework, Next.js, Tailwind CSS
Paradigms
Azure DevOps, DevOps, Continuous Integration (CI), Continuous Delivery (CD), Microservices, DevSecOps, Serverless Architecture, Test Automation, Event-driven Architecture, Testing, Model Context Protocol (MCP), Real-time Systems, Load Testing, Enterprise Application Architecture
Platforms
Kubernetes, AWS IoT, Azure, Google Cloud Platform (GCP), Oracle Cloud Infrastructure (OCI), Docker, Amazon Web Services (AWS), Azure Marketplace, Linux, AWS Lambda, Amazon EC2, Debian, Ubuntu, Azure Functions, PagerDuty, Red Hat Linux, Salesforce, Apache Kafka, Sysdig, Vanta, OpenShift, Vercel
Storage
On-premise, Amazon S3 (AWS S3), Amazon Aurora, Amazon DynamoDB, Azure SQL, Azure Storage, Google Cloud, PostgreSQL, Databases, Datadog, Microsoft Entra ID, Elasticsearch, MySQL, Redis
Other
Microsoft Azure, Site Reliability Engineering (SRE), Infrastructure as Code (IaC), Virtual Private Cloud (VPC), Cloud, Cloud Security, Solution Architecture, CI/CD Pipelines, Cloud Architecture, Cloud Engineering, Cloud Platforms, Deployment, Full-stack Development, Software Development Lifecycle (SDLC), Web Security, AWS DevOps, Containerization, AWS Secrets Manager, Amazon Inspector, Amazon RDS, Incident Response, Technical Leadership, Leadership, Argo CD, AWS FinOps, Amazon GuardDuty, FinOps, NAT, DNS, AWS ECS Fargate, Identity & Access Management (IAM), Load Balancers, Cursor AI, Cloud Infrastructure, Networking, Monitoring, Database Optimization, VM, SSH, Virtual Machines, Infrastructure, Distributed Systems, Platform Engineering, Agentic Coding, Serverless, Google Cloud Platform, Incident Management, DataOps, GitHub Actions, Artificial Intelligence (AI), GitOps, Security, Large Language Models (LLMs), Model Deployment, Software Architecture, APIs, Automation Testing, Multi-tenant Architecture, Agentic Deployment, Machine Learning Operations (MLOps), AI Agent Orchestration, AI Agents, Agentic AI Systems, SOC 2, AI Tools, GPU Computing, Graphics Processing Unit (GPU), Kubernetes Event-driven Autoscaler (KEDA), Disaster Recovery (DR), Encryption, Observability, OpenTelemetry, Cloud Governance, Open Policy Agent (OPA), Policy as code (PaC), AWS SCP, Pulumi, AWS Security Hub, User Interface (UI), HIPAA, Power BI, Serverless GPUs, Salesforce CLI, Mobility, ChromaDB, MCP Server, Prometheus, K3s, Snyk, OWASP, Reinforcement Learning from Human Feedback (RLHF), Software Engineering, Enterprise Architecture, Supabase, Boto3, AI Agent Evaluation, LLM Evaluation, Benchmark Design, TensorRT-LLM, NVIDIA Triton
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