About the role

AI is changing how people find things. When someone asks ChatGPT or Perplexity a question, some brands show up and others don't. PingAura helps brands show up — and monetize that presence. Our flagship product is the AI Coworker, a real agent that does the work of an AEO team for our customers.

We are hiring an AI Product Engineer to own features end to end — where most of the value comes from how the AI behaves, not from CRUD. You will talk to customers, shape the product, write the code, and ship it.

We are a small founding team backed by 14 CXO angel investors, Google for Startups, and AWS, with paying enterprise customers and a product running in production every day.

Responsibilities

Own AI-powered features end to end — database schema through API through agent behavior through UI
Ship product where the hard part is making the LLM do the right thing: prompts, tool use, evals, fallbacks
Build and extend the AI Coworker, dashboards, audits, and visibility tools
Design data models and write performant queries against Postgres
Build server-side logic: API routes, background jobs, agent runners, third-party integrations
Write evals before you ship. Measure what good looks like, then prove it
Ship production code multiple times a day with proper testing and monitoring
Join customer calls and translate pain points into product improvements

You may be a good fit if

You have 2+ years building and shipping web applications across frontend and backend
You build with AI tools every day — Cursor, Claude Code, Codex, or comparable — and have opinions about how to use them well
You are comfortable with server-rendered frameworks, REST APIs, relational databases, and cloud infrastructure
You have worked with Postgres (or similar) and can write non-trivial queries, migrations, and schema designs
You write solid TypeScript — async patterns, error handling, type safety
You have built at least one feature where the core logic was a large language model call, and you know why "it works in the demo" is not the same as "it works in production"
You ship rather than plan — small things today over big things next month
You communicate clearly in a small, remote-first team

Strong candidates may also have

Production experience with Next.js Server Actions, React Server Components, or comparable server-rendered patterns
Experience integrating LLM APIs with tool calling, structured outputs, and streaming
Familiarity with Langfuse, Sentry, or comparable observability tooling
Exposure to GCP or AWS in production
Background in search, content, or marketing technology

What we work with

Language: TypeScript across the stack; Python for ML and eval tooling
Web: Next.js 16 (App Router), React 19, Server Actions, Tailwind, Shadcn UI
Database: PostgreSQL on Supabase with row-level security; pg_cron and pgmq for scheduled and queued work
Cache and rate limiting: Redis on Memorystore — caching, distributed rate limiting, queue patterns
AI: OpenAI, Gemini, and Anthropic via a multi-provider routing layer
Observability: Langfuse for LLM traces, Sentry for errors, plus standard cloud logging and monitoring
Cloud: GCP for compute, data, and storage; AWS for CDN
Workflow: Turborepo monorepo, pnpm, Cursor and Claude Code daily

Compensation

Competitive salary benchmarked for early-stage startups in India

Why this team

The problem is brand new and the team is small. You ship to real paying customers from day one, you work directly with the founders, and the decisions move fast.

AI Product Engineer