The role
The mid-level role is for someone who has shipped real features in a production team and is now ready to take on more ownership. You will be trusted with whole modules and will pair with both the senior engineer and the founder.
You will help us build the next wave of features inside the CholaVerse platform and the AI agent layer that sits on top of it. You will write real production code, you will wire up AI APIs to do measurable, useful work for our customers, and you will own features end to end.
This is a builder role. We do not separate "AI" from "the rest of the codebase." An AI engineer at CholaVerse is someone who can ship a feature from database to UI to AI logic, and who treats prompt design and eval discipline with the same seriousness as backend architecture.
What you will actually do
- Build new modules and features inside CholaVerse: API endpoints, database models, frontend screens, and the AI logic that powers them.
- Develop AI agents for customer-facing automations across SEO, marketplaces, customer service, inventory, social and ads — and increasingly for new verticals beyond e-commerce.
- Integrate AI APIs (Anthropic, OpenAI and others) for chat, classification, content generation, structured data extraction and tool use.
- Build scheduled background jobs in Python using CrewAI and LangChain for non-real-time workloads.
- Translate fuzzy business problems — "we want the platform to automatically respond to delivery-delay enquiries" — into shipped, monitored features.
- Help us evaluate, monitor and improve AI output quality over time. Prompt iteration, eval sets, regression checks.
Our stack, so you know what you are walking into
- Frontend: React 19, modern build tooling, Tailwind-based design system.
- Backend: Express 5, Prisma, PostgreSQL.
- AI: direct Anthropic API for real-time chat assistants. Python with CrewAI and LangChain for scheduled agent workloads.
- Voice: Retell AI integrated with Twilio and Dialpad escalation, already live in the platform.
- Infra principle: client credentials live in database config tables, not .env files. Only system-level secrets sit in environment files.
What you bring
- Two to five years of professional engineering experience.
- Solid foundations in JavaScript or TypeScript, plus at least one of Node.js or Python for backend work.
- Working knowledge of relational databases and schema design (Postgres, Prisma or similar).
- Some experience with React or another modern frontend framework at production scale.
- Real experience using AI tools and LLM APIs to build something that ran in production, even if small.
- The ability to scope a non-trivial feature on your own and hold the timeline.
What we look for in all AI engineering roles
- Self-starter mentality. We do not micro-manage. You should be able to take a loose brief, ask the right clarifying questions and ship.
- Genuine curiosity about how AI systems behave: prompt design, context management, evals, multi-agent architectures.
- A bias toward simple, working software and away from over-engineered abstractions.
- Comfort with Git, modern dev workflows and reading other people's code.
- A real interest in joining a venture that wants to ship world-class AI products over the next few years, not a comfortable seat at a mature company.
How we will measure success
- Features shipped to production and adopted by customers.
- Quality of AI output on the workflows you own, measured against evals you help define.
- Speed and independence improving month over month.
- How much of the codebase you are confidently contributing to by month six.
Interested?
Send a short note — no five-page cover letters. Tell us what you have shipped, how you currently use AI tools, and your earliest start date.
Apply for this role
We reply within seven days, whether the answer is yes or no.