Ankur Goyal

About Ankur Goyal

DevOps Engineer with 14+ years of progressive experience designing and delivering enterprise-grade cloud platforms across Banking, Insurance, Life Sciences, and Enterprise Technology environments.I specialise in multi-cloud architecture (AWS, Azure, GCP), Kubernetes orchestration, CI/CD automation, DevSecOps, SRE practices, and — more recently — AI/MLOps engineering including ML pipeline automation, LLM/GenAI integration, and model deployment on Azure ML and AWS Bedrock.Throughout my career I have worked across India, the Netherlands (ING Bank, Amsterdam), and Australia (Melbourne), giving me broad exposure to enterprise engineering cultures, regulatory environments, and global delivery models. What I bring:• Designed and managed DevOps platforms supporting 200+ applications • Reduced deployment failures by 35%, MTTR by 25%, and cloud costs by 15–18% across multiple engagements• Implemented MLOps pipelines using Kubeflow, MLflow, Azure ML, and AWS Bedrock• Integrated LLM/GenAI solutions using Azure OpenAI for claims processing and document summarization• Led Disaster Recovery strategies achieving RTO reductions from 4 hours to 45 minutes• Mentored and upskilled engineering teams across Melbourne, Amsterdam, and India Experience across. AIA Australia · Bendigo & Adelaide Bank,Australia(Contractor) · ING Bank Netherlands(Contractor) · MavenWave · Publicis Sapient (Bridgestone, Nissan)-Contractor · SirionLabs Certifications: AWS Certified Solutions Architect – Associate Microsoft Azure AZ-900 Google Associate Cloud Engineer RedHat Certified Engineer (RHCE)Open to:Senior DevOps, Platform Engineering, MLOps, and Cloud Architecture opportunities across India.

Experience

1. Devops Engineer

   AIA Australia

   Jul 2024 — Present

   AI/MLOps Engineering: • Built end-to-end ML pipelines using Kubeflow on AKS for actuarial and risk scoring models; deployed model serving via MLflow and Azure ML with A/B testing capabilities. • Integrated Azure OpenAI Service for AI-assisted claims processing and policy document summarization, reducing manual review time significantly. • Built AI infrastructure on Azure ML and AWS Bedrock including GPU clusters, feature stores, and automated retraining pipelines triggered by model drift detection.Platform Engineering & CI/CD • Led DevOps platform supporting 200+ applications; standardized CI/CD pipelines reducing deployment failures by 35% and build time by 30%. • Implemented DORA metrics across all pipelines; improved deployment frequency by 40% and reduced MTTR by 25% via rollback automation. • Led Bitbucket to GitHub migration, cleaning up 800+ unused repositories and reducing licensing cost by ~20%. • Designed reusable Jenkins shared libraries adopted by 30+ teams; mentored 6+ engineers.Azure & AWS Cloud Infrastructure: • Managed Azure cloud services including AKS, Azure Monitor, Azure Key Vault, and Azure Container Registry to support enterprise workloads at AIA. • Leveraged AWS services including EC2, S3, IAM, CloudWatch, and AWS Bedrock for AI/ML infrastructure and supporting cloud workloads.Kubernetes, Observability & DevSecOps: • Managed AKS clusters with 99.95% uptime SLA; implemented HPA, Cluster Autoscaler, and Helm chart standards across all microservices. • Integrated Prometheus & Grafana for SRE observability; embedded SonarQube, Veracode, and Nexus IQ into pipelines reducing vulnerabilities by 45%. • Managed all production changes via ServiceNow CAB; sprint tracking in Jira; architecture docs in Confluence.Stack: AWS, AKS, Jenkins, GitHub Actions, Helm, Terraform, Prometheus, Grafana, MLflow, Kubeflow, Azure ML, AWS Bedrock, Azure OpenAI, SonarQube, Veracode, Jira, ServiceNow

Education

• Compucom Institute of Information Technology & Management(Engg. College)

  Bachelor Of Computer Applications, Computer Science

  2007 — 2010