Senior Full-Stack Software Engineer — Python

Ignyte is seeking a highly experienced Senior Full-Stack Software Engineer to design, build, integrate, deploy, and maintain software across a diverse technology environment.

This is a senior individual-contributor role for someone who can take a business objective or loosely defined requirement and turn it into a working production solution with minimal supervision.

The engineer will work under the architectural direction of a highly experienced senior technical leader while maintaining substantial ownership over implementation, delivery, and production support.

The role spans customer-facing applications, internal tools, integrations, cloud infrastructure, structured data, workflow automation, and AI-enabled software.

Key Responsibilities

• Build and enhance full-stack web applications
• Develop modern frontend applications using React
• Build backend services, APIs, integrations, and automation using Python
• Design and maintain PostgreSQL databases
• Develop and manage applications and infrastructure in Google Cloud Platform
• Build integrations using REST APIs, JSON, webhooks, OAuth, and third-party services
• Develop solutions using Google Workspace APIs, including Calendar, Gmail, Drive, Sheets, and related services
• Build and maintain headless CMS and modern web architectures
• Extend, troubleshoot, and modernize existing applications and codebases
• Build internal business applications and operational tools
• Translate business workflows into scalable software and automated processes
• Develop AI-enabled applications, workflows, and automation
• Implement structured data processing and validation
• Generate documents and other outputs from structured and unstructured data
• Implement CI/CD, automated testing, deployments, logging, and monitoring
• Troubleshoot production issues across frontend, backend, database, cloud, and integration layers
• Maintain secure, scalable, documented, and maintainable code
• Participate in architecture and technical design discussions
• Propose solutions and communicate technical tradeoffs clearly

Nature of the Engineering Work

Our engineering environment spans multiple products, technology stacks, and business systems.

Engineers are expected to be comfortable moving between new development and existing applications rather than working within one narrow technology or product.

Typical work may include:

• Customer-facing web applications
• Existing enterprise software
• Internal business applications
• Systems integration
• Workflow automation
• Cloud infrastructure
• Structured data processing
• AI-assisted applications
• Business process automation
• Production troubleshooting and modernization

The successful candidate must be comfortable switching between frontend, backend, database, infrastructure, integration, and AI-related work depending on business priorities.

Required Experience

• 10+ years of professional software development experience
• Significant professional engineering experience predating modern generative-AI coding tools
• Advanced Python experience
• Strong React frontend development experience
• Strong PostgreSQL and SQL experience
• Production experience with Google Cloud Platform
• Strong experience with REST APIs, JSON, webhooks, OAuth, and third-party integrations
• Experience with Google Workspace APIs
• Experience with headless CMS or similar modern web architectures
• Experience working with unfamiliar or inherited codebases
• Experience with Git, branching, code review, and CI/CD
• Practical DevOps and production deployment experience
• Strong debugging and troubleshooting capability
• Strong understanding of software architecture, scalability, security, and performance

This role requires flexibility across technologies.

The ideal candidate is comfortable learning and working within existing systems even when the technology differs from their primary stack.

Candidates should be capable of:

• Navigating inherited codebases
• Identifying technical debt
• Modernizing systems incrementally
• Selecting appropriate technologies based on the problem rather than personal preference

AI is expected to be a normal part of the software development process.

Candidates should have practical experience with some combination of:

• OpenAI, Claude, Gemini, or similar APIs
• AI-assisted coding tools
• LLM integrations
• Structured outputs
• Function and tool calling
• Retrieval-augmented generation
• Prompt and context engineering
• AI workflow automation

Candidates must understa