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About Ramakanth77
Hands-on Technical Lead with 15+ years in enterprise software. Builds Spring Boot services that connect applications to governed data, including healthcare records and banking risk systems. Uses AI coding assistants for prototyping and troubleshooting. Seeking AI application roles focused on backend integration, automation and secure data access.
Professional profile
- Location
- Bengaluru, India
- Time zone
- Asia/Calcutta
- Work mode
- Remote, Hybrid, On-site
- Availability
- Available Within 1 Month
- AI experience
- 4+ years
- Industry experience
- 16+ years
- Languages
- English, Hindi, Telugu, Tamil, Kannada
- Working hours
- 2:00PM to 11:00PM
- Typical response
- Same business day
- Preferred engagement
- Small (individual or single team)
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Proven on the network
Implementation records and publicly available work, where published.
0 AI Deployments delivered. No publicly identified implementations are available to inspect.
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What Ramakanth77 builds
Implementation domains listed on this profile. Evidence-supported items are identified separately below.
Specialisations
Agentic Workflow Automation
AI Application Development
AI Evaluation & Testing
AI Infrastructure & Platforms
Multi-Agent Systems
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AI Deployments
Real AI implementations demonstrated through evidence.
No publicly identified Deployments are available to inspect.
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Implementation capabilities
Evidence-supported means linked to a published Deployment or Case Study; other capabilities are Builder declared.
Evidence-supported
No published evidence linked yet.
Builder declared
- Agentic Workflow Automation
- AI Application Development
- AI Evaluation & Testing
- AI Infrastructure & Platforms
- Multi-Agent Systems
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Industry experience
Published Deployments support the listed counts. Other industries are Builder declared.
Agriculture
Builder declared
Banking
Builder declared
FinTech
Builder declared
Insurance
Builder declared
Payments
Builder declared
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Trust & verification
A closer look at how this profile and its evidence are reviewed.
Community Member
Published evidence is reviewed against the AI Deploy Network Evidence Standard.
How verification works
Verified Builder
Independently reviewed by AI Deploy Labs against the platform Evidence Standard.
How this is verifiedWhat the platform has established, and what remains builder-declared.
- Identity and organisation
- Identity checks confirm that the person presenting this profile controls the account and the professional identifiers attached to it, such as a LinkedIn profile. Organisation membership is confirmed by the organisation, not self-declared by the builder.
- AI Deployments
- An approved AI Deployment is an implementation record the builder submitted and the platform reviewed against the Evidence Standard before publication. Approval confirms the record is complete, coherent and consistent with the supporting material provided ā it is not an audit of the client's systems.
- Business outcomes
- Outcome figures are recorded by the builder on the deployment or case study that produced them, and are reviewed at publication. Aggregates shown on this profile are calculated from those approved records only.
- Evidence
- Supporting evidence comes from the records the builder published on this platform: approved AI Deployments, published AI Case Studies, verification outcomes and organisation participation.
- Currency
- Older evidence continues to count and is never removed. Recency is presented separately through Professional Currency so that current expertise can be assessed alongside historical work.
- Traceability
- Every figure on this profile can be followed to the record that produced it. Open the linked AI Deployment or AI Case Study to read the outcome exactly as it was reported.
The platform does not independently audit client systems or financial records. How this is verified
Professional record and further evidence
Client Portfolio
Portfolio startedHumana
Generative AI ā¢ Insurance
India2026ā¢ Built Spring Boot services for a healthcare data gateway. Added REST access alongside ODBC so applications could query enterprise sources through a governed interface. ā¢ Integrated Privacera encryption and decryption for sensitive patient and personal data. Configured Apache Ranger policies and mapped users and groups to data-access roles. ā¢ Integrated Azure Active Directory authentication for Azure SQL access and diagnosed TLS, connector and deployment failures across application and database boundaries. ā¢ Supported container deployments on Azure Kubernetes Service, reviewed code and demons
Ready to discuss your AI implementation?
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