The one-line version: You are a senior engineer embedded with one of Razorpay's largest merchants. You own their technical success end-to-end — from solutioning to go-live — and you do it with a stack of AI agents working alongside you. You are not a consultant, not a support engineer, not a solutions architect. You build, you ship, you own.

About the role

Razorpay's most strategic merchants — Nvidia, Airbnb, Meta, Shopify, and others — don't want a vendor. They want a partner/team who understands payments deeply, sits with their team, and makes their use cases work. That team comprises a Forward Deployed Engineer (FDE).

An FDE owns one merchant's technical destiny. You take a vague business ask and turn it into a concrete technical plan, then build and ship it — using both Razorpay's platform and our internal AI agents to move faster than any traditional team could. When you build something useful for one merchant, you feed the pattern back so the whole platform gets better.

This is modelled on the role pioneered by Palantir and now run at OpenAI, Anthropic, Databricks and Ramp — adapted for payments, and built AI-native from day one.

What you will do

- Own a merchant's technical success. You are the single engineering face the merchant sees. No "let me check with the team" handoffs.
- Scope and solution. Sit with the merchant's engineering and business teams, understand the real problem, and define a clear technical plan — ideally before the contract is signed.
- Build and ship. Write and review production code — in Razorpay's systems, and where allowed, in the merchant's repo. Custom flows, SDK integration, orchestration logic, server-to-server hooks.
- Use AI agents at full strength. Lean on coding agents for routine PRs, knowledge agents for merchant context, and routing agents for incident triage. You are expected to be the most AI-leveraged engineer in the org.
- Feed the platform.



When you build the same thing for 2+ merchants, take the pattern back to the product pods with a clear write-up.
- Keep the merchant informed. Run a regular progress cadence. Acknowledge merchant-raised issues within 2 hours. Never go silent.

What we are looking for

We hire for a "T-shaped" profile — deep engineering, broad execution. Roughly:

Weight

Area

What we expect

~50%

Engineering

Strong, hands-on coder. Python and one of Java/Go/TypeScript. Production-grade code, not prototypes.

~30%

Systems & deployment

APIs, webhooks, integration patterns, cloud (AWS/GCP), debugging across distributed systems. Comfort with payments flows is a strong plus.

~20%

Communication & ownership

Can explain a complex system to a non-technical merchant lead. Turns vague asks into clear specs. Owns problems end-to-end without being told.

Must-haves:

- SDE2+ level (4+ years for senior; exceptional candidates with less considered)
- Demonstrated end-to-end ownership — you have shipped something real, start to finish, ideally with customer contact
- Fluency with AI coding tools and agents — you already use them daily and can show how they multiply your output
- Comfort with ambiguity — you have worked without a transparent spec and made progress anyway
- Hands-on solutions architect or data/ML engineer background with real shipping experience

Why this role is worth it

- You will understand payments more deeply than almost anyone in India within two years.
- You will ship to production faster than anyone in the org — no five-team approval chains.
- You will have Senior leadership level visibility from day one, at Razorpay and at the merchant.
- You will be the most AI-leveraged engineer in the company, by design.

This role is not for everyone. It is for engineers who want depth, customer proximity, autonomy, and high stakes. If you want pure platform work with no customer contact, this is not it — and that is fine.

📌 Forward Deployed Engineer (Bengaluru)
🏢 Razorpay
📍 Bengaluru