Senior Python Developer

Neurealm; Gurugram District; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Neurealm is seeking an experienced Senior Python Developer to lead the design and development of scalable backend applications and distributed systems. The role emphasizes API design, backend architecture, and cloud integration, while mentoring teammates and driving best practices.

The position requires collaboration with product managers, architects, DevOps, and QA to deliver enterprise-grade solutions with a strong focus on quality, reliability, and performance.

Qualifications

• Expert-level Python programming experience.
• Experience with FastAPI, Flask, or Django.
• Designing and developing RESTful APIs and scalable microservices.
• Strong OO/SOLID design and asynchronous programming skills.
• Experience with AWS and containerized deployments (Docker, Kubernetes).

Responsibilities

• Design, develop, and maintain scalable Python applications.
• Architect backend systems, microservices, and RESTful APIs.
• Lead technical design discussions and drive architectural decisions.
• Review code and enforce coding standards and security practices.
• Optimize performance, scalability, reliability, and cost efficiency.
• Mentor junior developers through reviews and guidance.

Skills

Python

FastAPI

Flask

Django

RESTful APIs

OOP

SOLID

Microservices

Async programming

Leadership

Tools

AWS

Docker

Kubernetes

Git

PostgreSQL

MySQL

MongoDB

Redis

CloudWatch

CI/CD

Job description

We are looking for an experienced Senior Python Developer to lead the design and development of scalable, high-performance backend applications and distributed systems. The ideal candidate should possess deep expertise in Python, backend architecture, API development, cloud technologies (AWS preferred), and modern software engineering practices.

The role requires technical leadership, mentoring junior developers, driving architectural decisions, and collaborating closely with product managers, architects, DevOps, and QA teams to deliver enterprise-grade solutions.

Key Responsibilities

• Design, develop, and maintain scalable, secure, and highly available Python applications.
• Architect backend systems, microservices, and RESTful APIs following industry best practices.
• Lead technical design discussions and drive architectural decisions.
• Review code and ensure adherence to coding standards, security guidelines, and engineering best practices.
• Optimize application performance, scalability, reliability, and cost efficiency.
• Design database schemas and optimize complex SQL queries.
• Collaborate with cross-functional teams to define technical solutions and implementation strategies.
• Mentor junior developers through code reviews, technical guidance, and knowledge sharing.
• Troubleshoot complex production issues and perform root cause analysis.
• Drive automation through CI/CD pipelines and Infrastructure as Code
• Ensure applications are observable through proper logging, monitoring, and alerting.
• Participate in Agile ceremonies and contribute to sprint planning and technical estimation.
• Evaluate emerging technologies and recommend improvements to existing platforms.

Required Technical Skills

• Expert-level Python programming experience.
• Strong experience with FastAPI, Flask, or Django.
• Extensive experience designing and developing RESTful APIs.
• Strong understanding of Object-Oriented Programming (OOP), SOLID principles, and design patterns.
• Experience building scalable microservices architectures.
• Strong understanding of asynchronous programming (asyncio, FastAPI async).

Databases

• Strong knowledge of relational databases such as PostgreSQL, MySQL, or SQL Server.
• Experience with NoSQL databases such as MongoDB, DynamoDB, or Redis.
• Ability to optimize complex SQL queries and database performance.
• Hands-on experience with AWS services such as:
• Lambda
• ECS
• EC2
• S3
• API Gateway
• CloudWatch
• IAM
• SQS/SNS
• RDS
• Exposure to Azure or GCP is an added advantage.

DevOps & Deployment

• Docker and containerized application development.
• CI/CD using GitHub Actions, Jenkins, GitLab CI, or AWS CodePipeline.

Software Engineering

• Git and modern branching strategies.
• Unit, integration, and end-to-end testing (PyTest, Unittest).
• Strong debugging and performance tuning skills.
• Experience with Linux environments.
• Understanding of security best practices for APIs and web applications.

Good to Have

• Exposure to LLM frameworks such as LangChain, LangGraph, or LlamaIndex.
• Experience integrating with vector databases (Qdrant, Pinecone, FAISS, OpenSearch, etc.).
• Experience with event-driven architectures using Kafka, RabbitMQ, or AWS SQS.
• Knowledge of distributed systems and message-driven architectures.
• Familiarity with OAuth2, JWT, SSO, and authentication frameworks.
• Experience with monitoring tools such as Grafana, Prometheus, ELK Stack, or CloudWatch.
• Exposure to serverless architectures.

The successful candidate should demonstrate:

• Strong ownership and accountability for technical deliverables.
• Ability to mentor and guide development teams.
• Excellent analytical and problem-solving skills.
• Strong communication and stakeholder management abilities.
• Capability to balance technical excellence with business priorities.
• Ability to drive engineering best practices and continuous improvement.

Preferred Candidate Profile

We are looking for someone who:

• Has extensive experience building scalable backend platforms.
• Can independently design and implement complex technical solutions.
• Enjoys mentoring engineers and improving team productivity.
• Is passionate about software quality, automation, and performance.
• Keeps up to date with modern backend technologies and engineering practices.

Nice-to-Have (If Hiring for AI-Driven Teams)

Candidates with experience in the following areas will be preferred:

• Building AI-powered backend services.
• Developing Retrieval-Augmented Generation (RAG) applications.
• Integrating LLMs such as OpenAI, Claude, Gemini, or Amazon Bedrock into production applications.
• Developing scalable APIs that serve AI/ML workloads.