Back End Developer

SDE III – Backend Engineering | SaaS & AI Platforms

Experience: 6–9 Years

Location: Noida / Delhi NCR

Employment Type: Full-time

Function: Engineering / Platform Engineering

About the Role

We are looking for an experienced SDE III – Backend Engineering to build and scale high-performance backend systems for our SaaS and AI-led platforms.

This is a hands-on engineering role for someone who has worked on production-grade platforms at scale and understands how to design systems beyond just APIs. The person should be comfortable owning architecture, microservices, databases, cloud infrastructure, third-party integrations, payments, security, performance and reliability.

Experience working on SaaS, AI/GenAI platforms, developer platforms, media-tech or high-scale consumer technology products will be highly preferred.

What You Will Own

Backend & Platform Engineering

* Design, develop and scale backend services primarily using Node.js / TypeScript.

* Build production-grade REST APIs, asynchronous services and microservices.

* Own services from architecture and development through deployment, monitoring and production support.

* Design systems capable of handling high concurrency, large datasets and rapidly growing workloads.

* Drive API standardization, versioning, documentation, observability and performance.

SaaS Platform Architecture

* Build backend capabilities required for modern B2B and B2C SaaS platforms.

* Work on multi-tenant architecture, user management, roles and permissions, authentication and authorization.

* Build subscription, billing, entitlement, usage tracking, metering and quota systems.

* Design platform capabilities that can be exposed through APIs to internal and external customers.

* Understand API-first architecture and integration with third-party platforms.

AI & GenAI Platform Integration

* Build backend orchestration layers for AI/ML and GenAI workflows.

* Integrate AI models and third-party AI APIs into production applications.

* Build APIs around model inference, asynchronous AI jobs, job queues and workflow execution.

* Design systems for managing compute-intensive or long-running AI workloads.

* Work closely with AI/ML engineers to take models from experimentation to scalable production services.

* Implement usage tracking, token/credit consumption, rate limiting and cost monitoring for AI workloads.

Hands-on model training experience is not mandatory, but the candidate should understand how AI services are integrated, orchestrated and scaled within a production platform.

Databases & Data Architecture

Strong hands-on experience with:

* PostgreSQL

* MySQL

* MongoDB

* Redis

The candidate should understand:

* Database schema and data modelling

* SQL and query optimization

* Indexing and performance tuning

* Transactions and concurrency

* Database scaling and replication

* Caching strategies

* Relational vs NoSQL architecture decisions

Microservices & Distributed Systems

* Strong understanding of microservice architecture and distributed systems.

* Experience defining service boundaries and communication patterns.

* Experience with asynchronous/event-driven architecture.

* Exposure to technologies such as Kafka, RabbitMQ, SQS, Pub/Sub or similar systems.

* Understanding of idempotency, retries, distributed transactions, fault tolerance and graceful degradation.

* Ability to identify when a microservice architecture is appropriate versus unnecessary complexity.

Payments & Monetization

Hands-on experience integrating payment systems such as:

Stripe, Razorpay, PayU, Cashfree, Paytm or equivalent payment gateways.

Should understand:

* Payment gateway APIs

* Webhooks

* Subscription payments

* Recurring billing

* Payment reconciliation

* Refunds and cancellations

* Transaction states

* Failure and retry handling

* Secure payment workflows

Experience building monetization systems for SaaS subscriptions, credits/tokens, usage-based billing or digital products will be a strong advantage.

Cloud & DevOps

Strong working knowledge of AWS and/or GCP, including relevant services across:

* Compute

* Storage

* Databases

* Networking

* Load balancing

* Queues

* Serverless infrastructure

* Monitoring and logging

Hands-on exposure to:

* Docker

* Kubernetes

* CI/CD pipelines

* Git / GitHub / GitLab

* Infrastructure monitoring

* Production debugging

The candidate is not expected to replace DevOps/SRE but should be capable of independently understanding and troubleshooting production infrastructure.

Engineering Excellence

As an SDE III, we expect the candidate to contribute beyond individual feature development.

You will:

* Participate in architecture and system-design decisions.

* Conduct high-quality code reviews.

* Define coding and API standards.

* Identify technical debt and drive its resolution.

* Improve backend performance and reliability.

* Mentor junior and mid-level engineers.

* Troubleshoot complex production issues.

* Challenge weak technical approaches and propose scalable alternatives.

* Work closely with Product, AI, Frontend, DevOps, QA and Data teams.

Security & Reliability

Strong understanding of:

* OAuth / JWT

* Authentication and authorization

* RBAC

* API security

* Rate limiting

* Encryption

* Secrets management

* Data privacy

* Logging and audit trails

* OWASP fundamentals

Experience designing systems for high availability, fault tolerance, disaster recovery and production observability is preferred.

What We’re Looking For

Must Have

* 6–9 years of backend/software engineering experience.

* Strong hands-on expertise in Node.js and TypeScript/JavaScript.

* Strong API and backend architecture fundamentals.

* Production experience with microservices and distributed systems.

* Strong knowledge of PostgreSQL/MySQL and MongoDB.

* Experience with AWS and/or GCP.

* Hands-on experience with Git and modern development workflows.

* Experience building systems that have operated at meaningful production scale.

* Strong debugging and problem-solving capabilities.

* Ability to independently own a service or major platform component.

Strongly Preferred

* Previous experience building a SaaS platform.

* Experience with AI/GenAI products or AI API integrations.

* Payment gateway and subscription architecture experience.

* Redis and caching.

* Kafka/RabbitMQ or similar messaging infrastructure.

* Docker/Kubernetes.

* High-concurrency or high-transaction-volume platforms.

Good to Have

Experience working with:

* GenAI / LLM APIs

* AI inference infrastructure

* API gateways

* Vector databases

* WebSockets

* GraphQL

* Search infrastructure

* Media/video processing platforms

* CDN architecture

* Usage-based billing systems

* Observability platforms such as Grafana, Prometheus, Datadog or New Relic

What Makes Someone Successful in This Role

We are looking for an engineer who thinks like an owner, not someone who only executes tickets.

You should be comfortable asking:

Will this architecture scale?

What happens when this service fails?

How do we monitor it?

What happens at 10x traffic?

How do we reduce latency and infrastructure cost?

How should this service evolve over the next 2–3 years?

If you enjoy building products from 0→1 and then scaling them from 1→100, this role will give you significant engineering ownership.