Python Software Engineer

Shree Narayani Networking Solutions•Dallas, TX

About The Position

We are looking for an experienced Python Software Engineer to design, develop, and maintain scalable, high-performance software solutions. The ideal candidate should have strong hands-on expertise in Python development, backend engineering, API development, cloud technologies, and modern software engineering practices.

Requirements

Advanced proficiency in Python with strong knowledge of Python 3.x.
Strong understanding of object-oriented programming, data structures, algorithms, and design patterns.
Experience with Python frameworks such as FastAPI, Flask, or Django.
Strong experience developing REST APIs and microservices.
Good understanding of SQL and relational databases such as PostgreSQL, MySQL, or Oracle.
Strong knowledge of Git and version-control practices.
Experience with unit testing frameworks such as PyTest or unittest.
Knowledge of asynchronous programming using asyncio and related Python frameworks.
Experience with Docker and containerized application development.
Understanding of CI/CD and DevOps practices.
Strong debugging, problem-solving, and performance-optimization skills.
Proficiency in Python (preferred) or Java , with solid fundamentals (clean coding, testing, APIs, debugging, performance, and maintainability).
Working knowledge of at least one public cloud provider — AWS preferred —including hands-on familiarity with deploying/running services, IAM/security basics, logging/monitoring, and common managed services.
Practical exposure to AI/ML concepts and workflows (e.g., model integration patterns, basic ML lifecycle understanding, evaluation basics), sufficient to ramp into agent development with minimal hand-holding.
Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.
Typically 5+ years of software engineering experience, with strong hands-on Python development experience.
Experience working in Agile/Scrum development environments.
Strong communication and collaboration skills.
Ability to independently analyze complex technical problems and deliver scalable solutions.

Nice To Haves

Experience with NoSQL databases such as MongoDB, DynamoDB, or Redis is preferred.
Hands-on experience integrating with frontier model APIs (e.g., OpenAI or similar), including prompt design, tool/function calling, streaming, and reliability/cost considerations.
Familiarity with advanced agent architecture concepts such as memory , guardrails/assurance , and MCP (Model Context Protocol) or similar patterns for tool interoperability.
Experience with conversational/agent frameworks or platforms , such as LangGraph , CrewAI , Rasa , Decagon , or equivalent orchestration frameworks, including building multi-step workflows and tool-based agents.
Experience designing highly scalable distributed systems.
Knowledge of system design and software architecture.
Experience with event-driven and asynchronous architectures.
Experience in financial services, enterprise applications, or other large-scale environments.
Exposure to security, observability, and performance engineering.

Responsibilities

Design, develop, test, and maintain scalable applications and backend services using Python.
Build robust and reusable components, APIs, microservices, and integrations.
Develop RESTful APIs and integrate with internal and external systems.
Write clean, maintainable, well-tested, and production-ready code.
Troubleshoot complex technical issues and optimize application performance.
Work with databases, data models, caching, and asynchronous processing.
Implement secure coding practices, authentication, authorization, and API security.
Collaborate with Product Managers, Architects, DevOps, QA, and other engineering teams.
Participate in code reviews, technical design discussions, and architecture decisions.
Develop automated unit, integration, and functional tests.
Work with CI/CD pipelines and modern DevOps practices.
Monitor applications in production and support troubleshooting and root-cause analysis.
Contribute to technical documentation and engineering best practices.