Senior Full-Stack Software Engineer — Python / React / GCP / AI

Ignyte Assurance Platform™; Buenos Aires; Presencial; ARS 2.000.000 - 3.200.000; Jornada completa

Descripción de la vacante

Ignyte is seeking a highly experienced Senior Full-Stack Software Engineer to design, build, integrate, deploy, and maintain software across a diverse technology environment. The role is a senior individual-contributor position with ownership over implementation, delivery, and production support across customer-facing and internal applications.

The ideal candidate will have 10+ years of experience, strong Python and React skills, and production experience with Google Cloud Platform, REST APIs,

Formación

• 10+ years of professional software development experience.
• 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.

Responsabilidades

• 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.

Conocimientos

React

Python

PostgreSQL

REST APIs

Google Cloud Platform

AI/ML tooling

DevOps

CI/CD

Security

Web security

Herramientas

Git

CI/CD tooling

Descripción del empleo

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 understand software engineering fundamentals independently of AI-generated code and be capable of reviewing, debugging, testing, and improving AI-assisted implementations.

We are looking for someone who uses AI to increase engineering productivity, not someone who depends on AI to understand the software they are building.

Systems Integration

A significant portion of the role involves connecting applications and business systems.

Candidates should be comfortable designing workflows involving:

• REST APIs
• JSON
• Webhooks
• Authentication and OAuth
• Event-driven processing
• Business rules
• Scheduled processes
• Retry logic
• Logging and monitoring

Experience integrating platforms such as Google Workspace, CRM systems, accounting systems, cloud platforms, databases, and third-party SaaS applications is highly desirable.

Structured Data & Automation

The engineer should be comfortable building systems that transform information between multiple formats and systems.

This may include:

• Converting structured and unstructured information into validated JSON
• Data validation
• Schema-driven processing
• Workflow orchestration
• AI-assisted data extraction and transformation
• Human review and approval workflows

DevOps & Production Ownership

Engineers are expected to own work beyond code completion.

Responsibilities include:

• Testing
• Deployment
• CI/CD
• Monitoring
• Troubleshooting
• Documentation
• Performance optimization
• Production support

The engineer should be capable of taking work from development through stable production deployment.

Security

Candidates should understand secure software development practices, including:

• Authorization
• Role-based access
• Secrets management
• API security
• Audit logging
• Least-privilege access

Prior cybersecurity or compliance experience is useful but not required.

Working Style

This role requires significant independence.

The engineer may receive a business requirement such as:

“We need these systems connected and this workflow automated.”

They should be able to:

• Understand the business objective
• Investigate the existing environment
• Identify technical requirements
• Design an implementation approach
• Identify APIs and dependencies
• Develop the solution
• Test it
• Deploy it
• Document it
• Support it in production

The engineer will receive architectural guidance from senior technical leadership but should not require detailed technical tickets or step-by-step development instructions.

We expect engineers to bring proposed solutions, identify risks early, and ask focused questions when necessary.

Communication

• Excellent written and spoken English is required
• Must communicate technical decisions clearly
• Must be comfortable working directly with business leadership
• Must explain technical tradeoffs to non-technical stakeholders
• Must proactively communicate blockers, risks, and dependencies
• Must document systems and important technical decisions

Technical Assessment

Final candidates will complete a practical technical assessment.

The assessment may evaluate:

• API integration
• JSON and structured data
• Ability to interpret incomplete business requirements

The assessment will focus on realistic engineering work rather than algorithm puzzles.

Ideal Candidate

The ideal candidate is a senior engineer who has spent years building production software before AI coding assistants became common and now uses modern AI tools aggressively to improve productivity.

They are:

• Technically strong
• Highly independent
• Pragmatic
• Comfortable across multiple technology stacks
• Capable of understanding existing systems quickly
• Comfortable moving between product development and automation
• Able to turn ambiguous business requirements into working software
• Comfortable taking technical direction while independently owning execution

This is not a narrowly defined frontend, backend, or DevOps position.

We are looking for a broad senior engineer capable of owning complex software problems across the stack.