SDE III - Fullstack

GreyLabs AI; Bengaluru; On-site; INR 4,000,000 - 9,000,000; Full time

Job summary

GreyLabs is seeking an SDE 3 to own complex engineering bets end-to-end, from design docs to architecture decisions and shipping production code. You'll work across Voice AI Agents and Voice Analytics to build scalable backend services.

You will mentor juniors, contribute to API design, observability, testing, and incident response, and operate in a growing startup with new playbooks.

Qualifications

• 5-8 years of engineering experience with a track record of owning and shipping complex systems.
• Deep backend expertise: distributed systems in production; familiarity with failure modes at scale.
• Strong Python (Django) and Go for production code.
• Solid frontend experience with React.js and modern frontend development.
• Working knowledge of AWS (EC2 S3, Lambda, RDS, or equivalents).
• Strong fundamentals in relational databases (PostgreSQL preferred), data modeling, and query optimization.
• Led technical design: wrote design docs, ran reviews, and owned architecture decisions cross-functionally.
• Appetite for learning in a growing startup and tackling new problems.

Responsibilities

• Own complex engineering problems end-to-end from scoping and design through implementation, testing, and production operations.
• Write technical design documents, lead design reviews, and make architecture calls.
• Identify and resolve cross-cutting challenges: latency, reliability, security, and scalability across the platform.
• Collaborate with product teams to translate requirements into technical solutions and push back when needed.
• Mentor SDE1 and SDE2 engineers through code reviews and design feedback.
• Evolve engineering standards, API design, observability, testing, and incident response.

Skills

Python

Go

Django

React.js

AWS

PostgreSQL

Data modeling

Design docs

Architecture

CI/CD

Docker

Kubernetes

Tools

Docker

Kubernetes

GitHub Actions

Job description

SDE 3 at GreyLabs means owning technical bets end-to-end: writing the design doc, making the architecture call, and shipping it. You'll work across Voice AI Agents (our flagship autonomous voice platform) and Voice Analytics (conversation intelligence for CXOs).

Responsibilities

• Own complex engineering problems end-to-end from scoping and design through implementation, testing, and production operations, including personally driving resolution of production incidents.
• Write technical design documents, lead design reviews, and make architecture calls.
• Identify and resolve cross-cutting technical challenges: latency, reliability, security, and scalability across the platform.
• Work with product teams from problem definition to translate requirements into clean technical solutions and push back where the trade-offs warrant it.
• Mentor SDE1 and SDE2 engineers through code reviews, design feedback, and structured pairing.
• Evolve engineering standards, API design, observability, testing, and incident response.

Requirements

• 5-8 years of engineering experience; track record of owning and shipping complex systems.
• Deep backend expertise: designed and operated distributed systems in production; familiar with failure modes at scale.
• Strong Python (Django) and Go for production systems' idiomatic, performant code.
• Solid experience with React.js and modern frontend development.
• Working knowledge of AWS (EC2 S3, Lambda, RDS, or equivalents).
• Strong fundamentals in relational databases (PostgreSQL preferred), data modeling, and query optimization.
• Led technical design: wrote design docs, ran design reviews, and owned architecture decisions cross-functionally.
• An appetite for learning and figuring things out at a growing startup in an emerging category, where the problems are often new, and the playbook is still being written.

Strong Signals

• Voice AI stack in production: Deepgram, Whisper, AWS Transcribe, ElevenLabs, Google TTS, or equivalent ASR/TTS tools.
• LLM orchestration (LangChain, LlamaIndex, or custom) in a production voice or conversational AI system.
• Streaming or event-driven architectures.
• BFSI-adjacent domain experience: compliance monitoring, audit trails, and data sensitivity requirements in practice.
• Containerization and CI/CD: Docker, Kubernetes, and pipeline tooling (GitHub Actions, Jenkins, or equivalent).