Sr. Python Developer

Neurealm; Maharashtra; On-site; INR 1,800,000 - 2,800,000; 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 in Pune, India. The role emphasizes Python expertise, API development, cloud technologies (AWS preferred), and strong software engineering practices.

You will mentor juniors, drive architectural decisions, and collaborate with product managers, DevOps, QA, and architects to deliver enterprise-grade solutions.

Qualifications

• Expert-level Python programming experience.
• Strong experience with RESTful APIs.
• Experience designing and developing microservices architectures.
• Cloud experience with AWS preferred.
• CI/CD and automation experience.

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 ensure coding standards and security guidelines.
• Drive automation through CI/CD pipelines and IaC.
• Ensure observability through logging, monitoring, and alerting.

Skills

Python

API design

Microservices

AWS

CI/CD

Tools

Docker

Kubernetes

GitHub Actions

Jenkins

Job description

Experience Required

6 - 7 years

Location

• Pune, Maharashtra, India (PUN)

Job Summary

Office location : Gurgaon

Job Description – Senior Python Developer

Experience: 6–7 Years

Role Overview

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

Programming & Backend

• 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.

Cloud (Preferred)

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.
• Kubernetes fundamentals.
• 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

• Experience developing AI/ML or Generative AI applications.
• 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.

Leadership Expectations

• 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.

Has Hands-on Cloud Development Experience (AWS Preferred).

Is passionate about software quality, automation, and performance.

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.
• Agentic AI frameworks (LangGraph, CrewAI, AutoGen, etc.).
• MCP (Model Context Protocol).
• Integrating LLMs such as OpenAI, Claude, Gemini, or Amazon Bedrock into production applications.
• Developing scalable APIs that serve AI/ML workloads.