
KAVIA AI | Prompt to Working Product KAVIA is an AI-powered platform reinventing how software gets built—making product development radically faster, simpler, and more accessible. With just a…

KAVIA AI | Prompt to Working Product KAVIA is an AI-powered platform reinventing how software gets built—making product development radically faster, simpler, and more accessible. With just a…
What they do: LLM-powered platform that automates the software development lifecycle to generate and manage production-grade applications from prompts
Founded / HQ: Founded 2024; San Francisco, California
Stage / funding: Pre-Seed; $1.0M announced (Oct 2024)
Team size: Early-stage (~16 employees reported)
CEO / Founder: Labeeb Ismail
Software development lifecycle automation; code modernization for enterprise codebases.
2024
Enterprise AI / Software Development Tools
$1,000,000
Company announcement states investors were industry veterans, current and former CEOs, and friends & family; no lead VC publicly named.
| Company |
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Software Engineer – AI-Native Product Platform
Company:
KAVIA AI
Location:
India (Remote)
Type:
Full-time
Compensation:
₹16–25 LPA
About KAVIA AI
KAVIA AI is an enterprise software company building a production AI-native platform
used today by real teams on real, large-scale codebases.
We are creating an AI-native workflow and reasoning layer for the entire software development lifecycle
— from requirements and architecture to code generation, testing, CI/CD, and long-term evolution. Unlike point tools or copilots, KAVIA is designed to understand, reason about, and operate on entire systems over time
, not just individual prompts or files.
At the core of the platform are:
Agent-based orchestration systems
that plan, execute, and validate work across the SDLC
Enterprise knowledge graphs
that represent code, architecture, requirements, and decisions
KAVIA is already deployed in production environments and used by enterprise customers. As the platform and customer footprint grow, we’re hiring engineers to help scale, harden, and evolve the core systems that power KAVIA.
The Role
This is a hands-on software engineering role
on an existing, production AI platform.
As a Software Engineer
, you’ll work closely with senior engineers and the founding team to design, implement, and operate core backend systems, frontend interfaces, and AI-native workflows
that are already used by enterprise customers.
You’ll contribute directly to foundational platform components, gain exposure to real architectural tradeoffs, and gradually take ownership of meaningful subsystems. This role is ideal for engineers who want to work on serious, long-lived systems
and learn how modern AI-native platforms are built responsibly.
What You’ll Do Build and Evolve the Platform
Implement backend services and APIs that power KAVIA’s AI-native workflows
Contribute to agent-based orchestration systems that plan and execute complex tasks
Work with knowledge-graph-driven representations
of code, workflows, and metadata
Extend, refactor, and harden systems already running in production
Hands-On Engineering
Production & Operations
Collaboration & Growth
What We’re Looking For Required
~3+ years of professional software engineering experience
Strong Plus
Experience with Docker, Kubernetes, Terraform, and CI/CD pipelines
Experience with MongoDB
and AWS-based infrastructure
Experience using AI tools as part of your own development workflow
Why This Role Is Interesting
Work on a real, production AI platform
— not prototypes or experiments
Learn how AI-native systems are designed, built, and operated at scale
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Full lifecycle traceability
, enabling teams to understand why
software exists and how
it evolves
Strong backend engineering fundamentals, especially with Python
Experience building APIs and backend services used in production
Experience working with React or Next.js
-based frontend systems
Familiarity with data storage systems (relational databases and modern data stores)
Experience deploying and operating services in a cloud environment
Comfort working in a fast-moving environment with real users and real constraints
Experience operating production systems with uptime and reliability requirements
Startup experience or ownership of systems beyond just feature delivery
Be close to architecture, product decisions, and long-term technical direction
Solve hard problems at the intersection of AI, systems engineering, and enterprise software
Build infrastructure and workflows that real engineering teams depend on every day