Engineering the cloud platforms enterprises run on.
Fourteen years designing, securing and scaling Java platforms on Azure, AWS and Oracle — today leading engineering for MetLife’s claims-processing platform, and before that building Oracle Fusion CRM for Fortune 500 customers.

Enterprise engineering since 2012
- MetLifeNow
- Oracle2012–2023
- NetApp2015–2017
About / 01
Systems that scale, stay secure, can be observed — and can be changed safely. Simple to state. Hard to do well. That’s the work.
I’m a lead software engineer who has spent more than a decade building and modernizing the kind of enterprise systems people depend on without ever seeing them — the ones that process insurance claims, run CRM for global companies and support government and healthcare programs.
At MetLife I own backend architecture, cloud infrastructure and data engineering for the claims-processing platform, and I led modernization for the Disability and Absence Insurance technology maturity platform. Before that, nearly seven years as a Principal Software Engineer at Oracle shipping Fusion CRM features, AI-driven recommendations and release automation.
I bring the same standard to the people I work with — through architectural guidance, code-review practices and mentoring — and I use AI tools like GitHub Copilot every day to build better software, faster.
Building enterprise software at MetLife, Oracle and NetApp
Query performance gained through SQL and Oracle query-plan tuning
Downstream services brought under OAuth 2.0 and API governance
Professional credentials across AWS, Oracle Cloud and Java
Selected impact / 02
Hard problems, solved properly.
Six pieces of work, told as problem, approach and result. Details are limited to what can be shared publicly.
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MetLife ArchitectureScale-out
Horizontal scaling for high-volume claims workflows
A claims platform rebuilt as containerized microservices.
Challenge
High-volume insurance claims workflows that needed more resiliency and room to grow.
Approach
Architected and deployed the claims-processing systems as Java Spring Boot microservices on Azure Kubernetes Service.
Result
Improved resiliency and horizontal scale across claims workflows.
JavaSpring BootAKSAzure DevOps -
MetLife Security10+
Downstream services under one access model
Consistent, centrally governed access to every API.
Challenge
Consistent access control across the many services that consume the platform’s APIs.
Approach
Implemented OAuth 2.0 authentication flows and centralized API governance in Azure API Management.
Result
Reduced unauthorized-access exposure across 10+ downstream services.
OAuth 2.0Azure API ManagementAPI governance -
MetLife Performance80%+
Query performance improvement
Making a data-heavy platform feel fast again.
Challenge
Slow queries and response times in a data-heavy claims platform.
Approach
Rewrote and tuned SQL, optimized Oracle query plans and introduced Redis caching.
Result
80%+ query performance gains and lower average response times.
OracleSQL · PL/SQLQuery plansRedis -
MetLife Reliability↓ MTTR
Earlier detection, faster resolution
One view of a platform that spans Azure and AWS.
Challenge
Seeing and resolving incidents across a platform running on two clouds.
Approach
Built end-to-end observability pipelines across Azure Monitor and AWS CloudWatch and enabled Azure–AWS integration.
Result
Proactive incident detection, lower MTTR and a multi-cloud setup that supports enterprise SLAs.
Azure MonitorAWS CloudWatchMulti-cloud -
Oracle Applied AISmarter leads
For Fortune 500 users of Oracle Fusion CRM
Helping sales teams decide what to work on next.
Challenge
CRM users needed help deciding which leads to prioritize.
Approach
Introduced AI-driven recommendation and analytics features into Fusion CRM lead and decision workflows.
Result
Better lead prioritization, with higher engagement and sales conversion.
Oracle Fusion CRMREST APIsMachine learning -
Oracle AutomationCRM · ERP · HCM
Three cloud product lines, one release platform
Taking the manual work out of shipping patches.
Challenge
Manual, overhead-heavy patch and change deployment across several cloud product lines.
Approach
Built an internal automation platform with predictive deployment logic and ML-backed Python regression testing.
Result
Removed manual release overhead and reduced regression risk across releases.
PythonML-backed testingRelease engineering
Journey / 03
Fourteen years, four chapters.
Insurance, enterprise SaaS, storage and public-sector consulting — each role a step closer to the architecture, the data and the people who ship it.
Chapter four — Leading
Lead Software Engineer / Lead Data Engineer Current
MetLife · Claims-processing platform
Owning backend architecture, cloud infrastructure and data engineering for the platform that processes MetLife’s insurance claims.
- Architecture — Spring Boot microservices on AKS for resiliency and horizontal scale
- Security — OAuth 2.0 and API governance in Azure API Management across 10+ services
- Reliability — observability across Azure Monitor and AWS CloudWatch, lower MTTR
Chapter three — Building at scale
Principal Software Engineer
Oracle · Fusion CRM SaaS
Built and extended Oracle CRM Fusion SaaS modules used by Fortune 500 customers and product lines with millions of end users.
- Platform — high-performance REST APIs and full-stack features across database, services and UI
- AI features — recommendation and analytics that improved lead prioritization and conversion
- Leadership — mentored engineers and set code-review standards adopted across the team
Chapter two — Platform depth
Senior Software Engineer
NetApp · Enterprise customer support portal
Enhanced NetApp’s enterprise support portal with better service workflows, automated notifications and scalable features — built for high availability and long-term maintainability in a distributed environment.
Chapter one — Foundations
Technical Software Consultant
Oracle · Healthcare & government
Delivered enterprise healthcare and government solutions across multiple jurisdictions, designing backend APIs and integrations for mission-critical clients.
Expertise / 04
The whole stack, end to end.
From the query plan to the cloud cluster to the team shipping it — grouped the way these pieces come together in real systems.
Cloud & Platform
Containerized workloads on Azure, cross-cloud integration with AWS, and delivery pipelines that keep releases routine.
Software Engineering
Java services and APIs, from microservice design through security.
Data Engineering
Fast, dependable data layers: query tuning, caching and Databricks.
AI in Enterprise Products
“An engineer who uses AI to build better software, faster.”
Recommendation and analytics features in CRM, ML-backed test automation in production release workflows, and AI-assisted engineering every day.
Enterprise Systems
Large enterprise applications, the integrations between them, and modernizing what’s already in place.
Technical Leadership
Setting direction for a platform and raising the bar for the team building it.
Credentials / 05
Certified, and still learning.
Certifications
- Azure Solutions Architect ExpertIn progress
- AWS Certified Cloud PractitionerAmazon Web Services · Verify on Credly ↗2023
- Oracle Cloud Infrastructure 2023 Certified Foundations AssociateOracle2023
- Oracle APEX FoundationOracle2023
- Oracle WebCenter Portal 11.1.1.8 Certified Implementation SpecialistOracle2016
- Java J2EE CertifiedNIIT Limited2008
- All 17 credentialsFull list with credential IDs on LinkedInView ↗
Education
- Master’s in Computer ScienceModern Education Society’s Nowrosjee Wadia College, Pune · First Class2007
- Bachelor’s in Computer ScienceAKI’s Poona College of Arts, Science & Commerce · First Class with Distinction2005
Recognition
- Oracle WebCenter Portal SpecialistOracle2016
- Syntel Value AwardSyntel Ltd2011
- Publication: Oracle ADF FrameworkTechnical publication
Contact / 06
Let’s build something that holds up.
For senior engineering and technical leadership roles, or a conversation about cloud, data and enterprise platforms — email me directly or connect on LinkedIn.
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