AI Deploy Network
RM

AI Deploy Network / Builder

Rishabh Makhija

Staff Software Engineer

IndiaBangaloreLeadAvailable for Advisory Work

Published evidence

1 AI Deployment

1 publicly identified

01

About Rishabh

Staff Software Engineer with 10+ years building backend systems and AI-powered developer tooling. I lead the India-based Engineering Productivity team at Cockroach Labs, where I've shipped an org-wide merge queue, an AI-powered code review pipeline with pluggable custom skills/agents (grew adoption from 4 to 26 repos, raised review-comment resolution from 45% to 75%), and a reconciliation-based two-way GitHub/Jira issue sync service. I also own our team's GCP infrastructure and review Terraform pull requests across engineering teams.

Professional profile

Location
Bangalore, India
Time zone
Asia/Calcutta
Availability
Available for Advisory Work
AI experience
2+ years
Industry experience
10+ years
Languages
English, Hindi
Working hours
4:00 PM – 12:30 AM IST

02

Proven on the network

Implementation records and publicly available work, where published.

1 AI Deployment delivered, including 1 publicly identified implementation available to inspect.

03

What Rishabh builds

Implementation domains listed on this profile. Evidence-supported items are identified separately below.

Specialisations

Agentic Workflow Automation

AI Agents

AI Infrastructure & Platforms

Builder-listed deployment types

  • AI Orchestration
  • Code Review Assistant
  • Internal Developer Tooling
  • Multi-Agent Systems

04

AI Deployments

Real AI implementations demonstrated through evidence.

01 / AI DeploymentPublished record

AI-Powered Code Review Pipeline for Engineering Teams

Designed and scaled an AI-powered pull request review pipeline that gives engineering teams automated, configurable code review feedback, growing adoption from 4 to 26 repositories.

Software & SaaS · AI Orchestration · Code Review Assistant · Internal Developer Tooling · Multi-Agent Systems

View Deployment

05

Implementation capabilities

Evidence-supported means linked to a published Deployment or Case Study; other capabilities are Builder declared.

Evidence-supported

  • AI Orchestration1 record
  • Code Review Assistant1 record
  • Internal Developer Tooling1 record
  • Multi-Agent Systems1 record

Builder declared

  • Agentic Workflow Automation
  • AI Agents
  • AI Infrastructure & Platforms

06

Technology

Technologies listed by the Builder, distinguished by published evidence.

Evidence-supported

  • Claude Code1 record
  • GitHub Actions1 record
  • Google Cloud1 record

Builder declared

  • Kubernetes
  • Terraform

07

Industry experience

Published Deployments support the listed counts. Other industries are Builder declared.

Software & SaaS

1 published Deployment

Cloud & Infrastructure Providers

Builder declared

Gaming

Builder declared

IT Services & Systems Integration

Builder declared

Media & Entertainment

Builder declared

08

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
Community

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 — 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

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