Full Stack Engineer

o1jobaid; India; Remote; INR 1,200,000 - 2,400,000; Full time

Job summary

Unknown company in India is seeking a developer with strong Python backend engineering and DevOps skills, plus React experience to handle frontend tweaks as needed.

The role focuses on building reliable APIs, optimizing databases, background processing, deployment infrastructure, and secure data handling in a remote startup setting. You will own features from development through production and contribute to cost-efficient AI integrations.

Qualifications

• Proven Python backend experience with FastAPI or similar.
• Strong PostgreSQL fundamentals: schema design, migrations, performance.
• Hands-on with Docker, Linux, cloud infra, CI/CD.

Responsibilities

• Build and maintain backend services using Python, FastAPI, Pydantic, SQLAlchemy.
• Design PostgreSQL schemas, manage migrations, optimize queries and indexes.
• Develop background jobs with Redis, Celery, APScheduler; ensure retries and recovery.
• Improve CI/CD pipelines, deployment, rollback procedures, and monitoring.
• Integrate AI services and connect frontend via React updates.

Skills

Python

FastAPI

Pydantic

SQLAlchemy

PostgreSQL

Redis

Celery

APScheduler

Docker

CI/CD

AWS

React

DevOps

Tools

Docker

Linux

AWS

GitHub Actions

Terraform

OpenAI API

pgvector

Job description

Experience: Nice to Have Prior Startup Experience

About the role:

We’re looking for a developer with strong Python backend engineering and DevOps skills, along with enough React experience to make frontend changes when needed.

Your primary focus will be building reliable APIs, improving database performance, managing background processing, and strengthening deployment infrastructure. You should be comfortable working in a startup environment, taking ownership of technical problems, and carrying changes from development through production.

What you’ll do

• Build and maintain backend services using Python, FastAPI, Pydantic, and asynchronous SQLAlchemy.
• Design PostgreSQL schemas, manage Alembic migrations, and optimize queries, indexes, and database connections.
• Develop reliable background jobs and scheduled workflows using Redis, Celery, and APScheduler, including retries and failure recovery.
• Build and improve CI/CD pipelines, automated checks, deployment processes, and rollback procedures.
• Manage Docker-based environments and support cloud infrastructure, including AWS RDS, S3, and SES integrations.
• Improve application logging, monitoring, alerting, and production troubleshooting.
• Strengthen authentication, authorization, secrets management, and secure handling of candidate data and uploaded documents.
• Integrate AI services and improve their reliability, response times, and operating costs.
• Make targeted React updates to connect APIs, improve user workflows, and resolve frontend issues.
• Write meaningful tests, review code, and document services and operational procedures.

What we’re looking for:

• Prior experience working in a startup, with ownership of backend services and deployments.
• Strong Python skills and hands‑on experience with FastAPI or a comparable Python web framework.
• Solid understanding of REST APIs, asynchronous programming, validation, authentication, and authorization.
• Strong PostgreSQL and SQL fundamentals, including schema design, migrations, transactions, and performance tuning.
• Practical experience with Docker, Linux, cloud infrastructure, and CI/CD.
• Experience deploying, monitoring, and troubleshooting production applications.
• Familiarity with background processing, caching, retries, and reliable integration with third‑party services.
• Clear communication, sound technical judgment, and the ability to work independently in a remote team.

Nice to have:

• AWS experience, particularly RDS, S3, SES, IAM, and CloudWatch.
• Infrastructure as code using Terraform or similar tools.
• GitHub Actions and automated deployment workflows.
• OpenAI API integrations, LangChain, LangGraph, or other AI application frameworks.
• Embeddings, semantic search, and pgvector.
• Experience with database backups, recovery procedures, and cloud cost optimization.
• Backend: Python, FastAPI, Pydantic, SQLAlchemy, Alembic
• Data and background processing: PostgreSQL, pgvector, Redis, Celery, APScheduler
• Infrastructure and tooling: Docker, Docker Compose, GitHub Actions, AWS integrations
• AI: OpenAI integrations, LangChain, LangGraph, sentence-transformers
• Automation: Chrome Manifest V3 extension, Node.js, Express, Playwright