apoorva.jaitly

Solutions Architecture // Cloud // AI Integrations // Bangalore, IN

Apoorva Jaitly

Solution Architect II, AdTech at Amazon | AWS and Kubernetes Specialist

I help enterprises and partners turn complex requirements into scalable, secure cloud and AI-powered solutions: 11+ years across solutions architecture, platform engineering, and enterprise consulting at Amazon, CrowdStrike, Atlassian, GE Digital, Boeing, and Accenture.

Open to relocation: Europe and Australia/NZ, visa sponsorship welcome

11+years in cloud & architecture
100+enterprise customers served
50%faster K8s support resolution
99.5%uptime SLA on K8s platforms

About

From platform engineering depth to partner-facing architecture

I started in cloud infrastructure at Accenture, building fault-tolerant AWS environments for enterprise clients, and spent 5+ years at Atlassian as a Senior Enterprise Solutions Architect advising Fortune 500 customers on Kubernetes, AWS, and cloud-native adoption. Today at Amazon Ads I design advertising technology solutions that help agency partners and retail media platforms integrate with Amazon Ads APIs, AI/ML ad features, and AWS services.


What I bring is the combination recruiters usually have to hire twice for: deep hands-on infrastructure skills (CKA certified, Terraform, EKS, CI/CD) and the customer-facing craft of discovery sessions, executive workshops, proof-of-concepts, and architectural reviews that move deals and adoption forward.

Core skills

The toolkit

Cloud platforms

AWS · EKSEC2IAM LambdaVPCS3 RDSRoute53CloudFormation GCP · GKEAzure

Containers & IaC

KubernetesHelmkubeadm DockerTerraform

DevOps & CI/CD

JenkinsBambooGit ArtifactorySonarQube PythonShell

AI, data & APIs

RAG pipelinesLangChainHugging Face ElasticsearchAWS AI services REST APIsMySQLPostgreSQLDynamoDB

Security & networking

SSO / SAMLOAuthLDAP IAMSSLVPC design Cloud misconfig analysis

Customer-facing craft

Technical discoveryExecutive workshops Proof-of-conceptsReference architectures Architectural reviews

Experience highlights

Where the numbers come from

Solution Architect II, AdTech

May 2026 - Present

Amazon, Bangalore

  • Accelerated partner onboarding velocity and time-to-value for agency partners and retail media platforms by designing advertising technology solutions leveraging Amazon Ads APIs, AI/ML ad features, and cloud-native AWS services.
  • Enabled scalable, secure, high-performance partner integrations by developing technical specifications, proof-of-concept implementations, and integration guides, and conducting architectural reviews against privacy, security, and performance standards.

Senior Enterprise Solutions Architect

May 2020 - Jan 2026

Atlassian, Bangalore

  • Reduced global Kubernetes support resolution time by 50% by revamping the worldwide Kubernetes Support Readiness training program and automating Bitbucket Data Center deployments on AWS EKS with Terraform, cutting provisioning from 3 days to 4 hours.
  • Designed Kubernetes platforms delivering a 99.5% uptime SLA for enterprise customers with 10,000+ users, architecting Docker and EKS-based solutions with Helm and integrating LDAP, SSO/SAML, and Elasticsearch.
  • Accelerated customer adoption by 40% through proof-of-concepts and reference architectures, delivering 50+ executive workshops and acting as trusted advisor to 25+ strategic enterprise accounts.

Cloud Infrastructure Architect

Nov 2014 - Aug 2018

Accenture, Bangalore

  • Ensured high availability and automated scaling for enterprise workloads serving 500,000+ users by designing fault-tolerant AWS environments with Terraform across EC2, VPC, RDS, S3, DynamoDB, Route53, SNS, SQS, and IAM.
  • Reduced manual provisioning effort by 60% by containerizing microservices with Docker and Kubernetes and automating CI/CD workflows through Jenkins pipelines and Python/Shell scripting.

Signature project

Production RAG pipeline for support intent classification

Built at Atlassian to bring AI-assisted retrieval into enterprise support workflows, combining retrieval-augmented generation with existing search infrastructure.

Problem

Enterprise support at scale meant high ticket volumes, slow intent triage, and rising API costs for every LLM call. Answers had to be fast, accurate, and grounded in real product documentation.

Approach

Designed a production RAG pipeline using LangChain for orchestration, Hugging Face models for embedding and classification, and Elasticsearch as the retrieval layer, with caching and routing to control LLM API spend.

Outcome

A retrieval system that classified support intent reliably at production latency while meaningfully cutting per-query cost, proving AI could sit inside enterprise support workflows.

92%intent classification accuracy
45%reduction in LLM API costs
<200msretrieval latency
LangChainHugging FaceElasticsearch PythonAWS

Certifications

Verified credentials

AWS

AWS Certified AI Practitioner

Amazon Web Services · Jan 2026

CKA

Certified Kubernetes Administrator

Cloud Native Computing Foundation · Oct 2024

ITIL

ITIL Certified

IT service management foundations

Contact

Let's talk about Solutions Architect opportunities

If you're hiring for Solutions Architect, Solutions Consultant, Cloud Engineer, or Partner Solutions roles in Europe, Australia, or New Zealand, and need someone who can architect enterprise cloud and AI solutions while owning the customer relationship, I'd love to hear from you. Open to relocation and visa sponsorship.