Sr. Python Developer

Neurealm Company; Chennai, Tiruchirappalli, Coimbatore District, Bengaluru, Hyderabad; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Neurealm Company in Chennai is seeking a Senior Python Developer to lead backend design and development of scalable, high-performance applications. You will architect microservices, RESTful APIs, and ensure security, reliability, and cost efficiency while mentoring teammates.

You should have deep Python expertise (FastAPI/Flask/Django), experience with cloud AWS, CI/CD pipelines, containers, and observability tools.

Qualifications

• 3–5 years of experience as a Python backend developer.
• Expertise in Python frameworks (FastAPI, Flask, Django).
• Experience designing and developing RESTful APIs.
• Strong understanding of OOP, SOLID principles, and design patterns.

Responsibilities

• Design, develop, and maintain scalable Python backends and microservices.
• Architect backend systems and RESTful APIs following best practices.
• Lead technical design discussions and drive architectural decisions.
• Mentor junior developers and ensure code quality, security, and performance.

Skills

Python programming

REST APIs

OOP & SOLID

Microservices

Async programming

Testing (PyTest/Unittest)

Tools

FastAPI

Flask

Django

PostgreSQL

MySQL

SQL Server

MongoDB

DynamoDB

Redis

AWS Lambda

EC2

S3

API Gateway

CloudWatch

IAM

SQS/SNS

RDS

Docker

Kubernetes

GitHub Actions

Jenkins

GitLab CI

AWS CodePipeline

Linux

Job description

## Sr. Python Developer07-11-2026 08:05:45Job\\_3049913 - 5 years* Chennai, Tamil Nadu, India (CHN)Job Description – Senior Python DeveloperExperience: 3–5 YearsRole OverviewWe 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 ResponsibilitiesDesign, 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 CodeEnsure 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 SkillsProgramming & BackendExpert-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).DatabasesStrong 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:LambdaECSEC2S3API GatewayCloudWatchIAMSQS/SNSRDSExposure to Azure or GCP is an added advantage.DevOps & DeploymentDocker and containerized application development.Kubernetes fundamentals.CI/CD using GitHub Actions, Jenkins, GitLab CI, or AWS CodePipeline.Software EngineeringGit 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 HaveExperience 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 ExpectationsThe 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 ProfileWe 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.Has hands-on cloud development experience (AWS preferred).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.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.