Founding Product Engineer – Full Stack & Applied AI

Location: Hyderabad

Employment Type: Full-time

Experience: 3–6 years The Role

We are looking for a Founding Product Engineer with solid full-stack and applied-AI experience.

Frontend, backend, databases, cloud, AI agents and evaluations—you should be comfortable moving across the complete product stack because real product problems do not respect technical boundaries.

You will work directly with the founders and take ownership of features from problem discovery to production impact. There are no long approval chains or narrowly defined responsibilities. You identify what matters, build it, ship it, measure the outcome and improve it.

Prototype quickly. Ship thoughtfully. Measure what changed. If it works, scale it. If it does not, learn and try something better.

This is not a role for someone who wants to work exclusively on frontend, backend or AI models. We need a product engineer who can own the complete system.

What You’ll Do

Build and ship AI-powered product features end-to-end across frontend, backend, database, AI workflows and cloud infrastructure.

Develop production frontend applications using Next.js, React and TypeScript.

Design and build scalable backend services using Python and FastAPI.

Design PostgreSQL schemas, relationships, migrations, indexes and optimized queries.

Build and integrate LLM applications, RAG pipelines, AI agents and workflow-automation systems.

Integrate APIs from OpenAI, Anthropic, Gemini or other leading model providers.

Develop evaluation systems to measure AI accuracy, reliability, latency, cost and business impact.

Personally deploy, monitor and support applications in production using AWS, Docker and CI/CD.

Work directly with founders, users and internal teams to identify real operational problems.

Build rapid prototypes, validate them with users and convert successful experiments into reliable production systems.

Use AI development tools such as Cursor, Claude Code, Codex, Windsurf or similar tools to increase development speed.

Set clear product metrics and measure whether your work improved conversion, engagement, efficiency, revenue or customer experience.

Troubleshoot production issues and remain accountable until the problem is resolved.

Explain technical decisions and product outcomes clearly to non-technical stakeholders.

Contribute to product,



architecture and engineering decisions as an early member of the team.

You Might Be a Good Fit If

You have previously worked as a Founding Engineer, early engineer or core product engineer in an early-stage startup.

You have built a product or major feature from zero to production.

You naturally work across frontend, backend, database, AI and deployment.

You have shipped AI-powered features used by real customers—not only personal projects, hackathons or demos.

You are comfortable starting with an unclear problem and creating structure independently.

You can work directly with founders without waiting for detailed instructions.

You use AI coding tools as part of your daily engineering workflow.

You can build and ship meaningful features within days or weeks.

You care about business and user outcomes, not only technical implementation.

You take ownership when something succeeds, fails or breaks in production.

You can explain why a metric moved and what you will do next.

Mandatory Requirements

Please apply only if you meet the following requirements:

3–6 years of professional full-stack or product-engineering experience.

Previous experience as a Founding Engineer, early-stage startup engineer or engineer with clear zero-to-one product ownership.

Proven ownership of at least one production feature across database, backend API, frontend and deployment.

Production experience with React and TypeScript.

Hands-on experience with Next.js is strongly preferred.

Strong Python backend-development experience.

Hands-on experience with FastAPI; Django or Flask may be considered if Python backend experience is strong.

Strong PostgreSQL experience, including schema design and database migrations.

Experience deploying and maintaining applications on AWS or an equivalent cloud platform.

Hands-on experience with Docker and CI/CD pipelines.

Experience personally shipping applications to production rather than handing them entirely to a DevOps team.

Experience integrating LLM APIs such as OpenAI, Anthropic or Gemini.





Experience building production AI features such as RAG systems, AI agents, intelligent workflows or automation pipelines.

Strong ownership, problem-solving and communication skills.

Important: This is a Python backend role. Candidates whose backend experience is limited to Node.js, Express.js or the MERN stack will not be considered.

Nice to Have

Voice AI, speech-to-text, text-to-speech or real-time systems experience.

Experience with LangChain, LangGraph, LlamaIndex or similar agent frameworks.

Experience with vector databases, embeddings, hybrid search or GraphRAG.

Experience building AI evaluation, observability or feedback systems.

Flutter or mobile-application development experience.

Stripe, payment-gateway or subscription-system experience.

Experience building workflow automation, operations platforms or event-technology products.

Experience working directly with customers, sales, service or operations teams.

Experience with Redis, queues, event-driven systems or microservices.

Experience with AWS ECS, EC2, RDS, S3, Lambda and CloudWatch.

What Success Looks Like

Within your first few months, you will:

Understand the product, users and business workflows.

Independently identify and solve meaningful product problems.

Ship complete AI-powered features into production.

Establish clear success metrics for the features you own.

Use production data and user feedback to improve what you build.

Reduce the time between identifying a problem and delivering a working solution.

Demonstrate measurable improvements in user experience, operational efficiency, engagement or revenue.

How We Work

Own the outcome: Your responsibility does not end when the code is merged.

Work across boundaries: Frontend, backend, AI and infrastructure are parts of one product.

Ship and learn: Release quickly, measure carefully and improve continuously.

Stay close to users: Understand the real problem before deciding what to build.

Use AI by default: AI is part of both our product and our engineering workflow.

Keep it practical: Choose the simplest reliable solution that creates measurable impact.

Communicate clearly: Share progress, risks, problems, decisions and results openly.

If you are a founding-minded product engineer who can build across the stack, ship AI-powered systems and take complete ownership of business outcomes, we would like to hear from you.

📌 Founding Product Engineer (Hyderabad)
🏢 Airawath
📍 Hyderabad