Python Principal Architect

Requirement/Must Have:

• 12+ years of hands-on experience in full stack development.
• Strong expertise in Python and SQL.
• Experience designing enterprise-grade applications.
• Hands-on experience with APIs and end-to-end system architecture.
• Strong experience with Google Cloud Platform, AWS, Docker, FastAPI, Django, and CI/CD.
• Ability to write production-quality code across the complete software lifecycle.
• Experience building reusable framework-quality components.
• Strong knowledge of architecture decision-making and trade-off analysis.
• Experience with observability, monitoring, and deployment of AI services.
• Expertise in designing scalable data ingestion and embedding pipelines.

Experience:

• 12+ years of software engineering and architecture experience.
• Proven experience architecting and delivering enterprise applications.
• Experience with AI frameworks and modern engineering practices.
• Experience working in regulated environments such as financial services or cybersecurity preferred.

Responsibilities:

• Design end-to-end system architectures and APIs.
• Define and own technical blueprints for new applications and platforms.
• Build scalable systems from data ingestion and embedding pipelines through production deployment and monitoring.
• Solve complex engineering problems and perform architecture trade-off analysis.
• Write and maintain production-quality Python, SQL, and API service code.
• Build reusable engineering frameworks and shared components.
• Develop CI/CD pipelines and Docker-based deployment strategies.
• Track and evaluate emerging AI technologies, frameworks, and tooling.
• Establish engineering standards including code reviews, testing practices, and reusable libraries.
• Conduct technical design reviews and mentor engineering teams on architecture best practices.
• Partner with Product, Data Science, and Platform Engineering teams.
• Communicate technical decisions and business impacts to stakeholders.
• Support compliance and data governance requirements in regulated environments.

Should Have:

• Strong understanding of AI frameworks such as LangGraph, Google ADK, CrewAI, or AutoGen.
• Experience with retrieval methods, fine-tuning techniques, and AI tooling.
• Strong leadership in technical design and engineering excellence.
• Ability to rapidly prototype and scale solutions into production systems.

Skills:

• Python.
• SQL.
• FastAPI.
• Django.
• API Development.
• Google Cloud Platform.
• AWS.
• Docker.
• CI/CD.
• System Architecture.
• AI Engineering.
• Observability and Monitoring.
• Full Stack Development.
• Cloud-Native Development.

Qualification and Education:

• Bachelor s degree in Computer Science, Engineering, or related field preferred.