Full-Stack Product Engineer — Platform & DevOps

Outsourced; Colombia; On-site; COP 120,000,000 - 240,000,000; Full time

Job summary

Outsourced is seeking a senior, AI-proficient full-stack product engineer with strong infrastructure, production, and DevOps experience. You will own both the application stack and the underlying infrastructure, tooling, and runbooks to ensure reliable deployment, operation, and support.

You will use AI-assisted engineering tools to speed development, debugging, and automation while maintaining sound engineering judgment.

Qualifications

• Senior software engineer with strong full-stack experience.
• Experience operating production systems in AWS or similar cloud environments.
• Proficiency with CI/CD pipelines, containers, infrastructure automation, monitoring, and incident response.
• Strong debugging across application, database, infrastructure, and network boundaries.
• Ability to use AI tools effectively for code development, troubleshooting, analysis, and automation.
• Comfort diagnosing unfamiliar production problems and making sound decisions with incomplete information.

Responsibilities

• Build and maintain full-stack product with the engineering team.
• Own and improve CI/CD, deployment workflows, and release reliability.
• Improve production observability, monitoring, alerting, logging, and incident diagnosis.
• Leverage AI-assisted tools to accelerate debugging and root-cause analysis.
• Act as technical owner for production incidents and customer-reported issues.
• Reproduce problems, identify root causes, and drive fixes to resolution.
• Improve AWS infrastructure, security, access controls, secrets management, networking.
• Automate repetitive operational tasks with conventional and AI-powered approaches.
• Establish runbooks and production-readiness standards.
• Help engineers safely take ownership of staging and production through tooling and guardrails.
• Identify recurring operational problems and implement durable improvements.
• Contribute to architecture and design decisions across the product.
• Use AI tools throughout development lifecycle including testing and documentation.
• Continuously evaluate AI/engineering tools to improve productivity and reliability.
• Collaborate with teams in the US, Latin America, and India.

Skills

Full-stack development

AI-assisted development

AWS production systems

CI/CD pipelines

Observability and incident response

Automation and infra tooling

Security fundamentals

Debugging across app/db/infra

Technical ownership

Tools

AWS

Terraform

CloudWatch

CodeBuild

S3

Job description

About The Role

We are looking for a senior, AI-proficient full-stack product engineer with strong infrastructure, production, and DevOps experience.

About The Role

We are looking for a senior, AI-proficient full-stack product engineer with strong infrastructure, production, and DevOps experience. You will work throughout the application stack, with additional ownership for the infrastructure, tooling, and operational practices that allow Engineering to deploy, operate, diagnose, and support the product reliably. We expect you to use modern AI-assisted engineering tools as an integral part of your work, accelerating software development, troubleshooting, infrastructure automation, and operational improvements while maintaining strong engineering judgment and accountability. A central goal of this role is to make engineering operations predictable, reliable, and increasingly automated. Deployments should be repeatable and accessible to the engineering team, production problems should be detected before customers report them, infrastructure should be understandable and maintainable, and engineers should have the tools and guardrails they need to safely own what they ship. You will play an important role in building an engineering organization that operates efficiently, scales reliably, and continuously improves through automation and AI-enabled tooling.

What you'll do

• Build and maintain full-stack product alongside the rest of the engineering team.
• Own and improve CI/CD, deployment workflows, and release reliability.
• Improve production observability, monitoring, alerting, logging, and incident diagnosis.
• Leverage AI-assisted tools to accelerate debugging, root-cause analysis, log investigation, and operational troubleshooting.
• Act as a technical owner for production incidents and customer-reported engineering issues.
• Reproduce problems, identify root causes, coordinate fixes where necessary, and drive issues through resolution.
• Improve AWS infrastructure, security, access controls, secrets management, networking, and operational hygiene.
• Automate repetitive operational tasks, using conventional automation and AI-powered approaches where appropriate.
• Establish practical runbooks, production-readiness standards, and incident-response practices.
• Help engineers safely take greater ownership of staging and production through improved tooling, automation, and operational guardrails.
• Identify recurring operational problems and implement durable, systemic improvements.
• Participate in application architecture, implementation, and technical design decisions across the broader product.
• Use AI-assisted engineering tools throughout the development lifecycle, including implementation, testing, code review, debugging, and documentation.
• Continuously evaluate emerging AI and engineering tools that can meaningfully improve developer productivity and production reliability.
• Collaborate across engineering teams in the US, Latin America, and India.

What we're looking for

• Strong professional software engineering experience, including meaningful full-stack development.
• Demonstrated proficiency with AI-assisted software development tools, such as Claude Code, Codex, Cursor, or equivalent, as part of everyday engineering workflows.
• Strong hands‑on experience operating production systems in AWS or a comparable cloud environment.
• Experience with CI/CD pipelines, containers, infrastructure automation, monitoring, and incident response.
• Strong debugging ability across application, database, infrastructure, and network boundaries.
• Ability to use AI tools effectively for code development, troubleshooting, analysis, and operational automation while independently validating results.
• Comfortable diagnosing unfamiliar production problems and making sound decisions with incomplete information.
• Strong understanding of security fundamentals, permissions, secrets, and production access.
• Ability to simplify and automate operational systems while maintaining reliability and security.
• Strong communication and judgment under pressure.
• Willingness to own a production issue from initial report through root cause and durable resolution.
• Curiosity and adaptability as AI capabilities and engineering practices continue to evolve.

Especially valuable

• Experience with ECS, Lambda, RDS/PostgreSQL, CloudWatch, S3, IAM, CodeBuild, or similar AWS services.
• Experience with Terraform, CloudFormation, or another infrastructure‑as‑code system.
• Experience applying AI to operational workflows, including incident investigation, log analysis, automated diagnostics, or infrastructure management.
• Familiarity with LLM APIs, agentic workflows, MCP, or AI‑powered developer and operational tooling.
• Experience operating SaaS platforms with customer‑facing integrations.
• Experience with Python, TypeScript/Node.js, PostgreSQL, or similar technologies.
• Experience improving engineering organizations by decentralizing release responsibilities, production access, and operational knowledge.
• Experience building internal developer platforms, self‑service tooling, or automated operational workflows.

How we work We expect engineers to own outcomes, exercise independent judgment, and use AI to accelerate delivery without compromising quality, security, or reliability. For this role in particular, success means creating an engineering environment where operational knowledge, tooling, and responsibility are shared across the team.

That Means

• Predictable delivery: Deployments become repeatable, reliable, and increasingly automated.
• Shared ownership: Engineers can safely deploy, operate, and support the services they build.
• Proactive operations: Production issues are detected early, observable, and readily diagnosable.
• Effective incident response: Customer‑reported problems are investigated systematically and resolved with clear ownership.
• Continuous improvement: Recurring incidents lead to durable improvements in architecture, tooling, and processes.
• AI‑enabled productivity: AI is used throughout development and operations to accelerate problem‑solving, automate repetitive work, and improve engineering effectiveness.
• Operational simplicity: Infrastructure is understandable, documented, secure, and maintainable.
• Engineering independence: Routine operational work is handled efficiently by the team, with minimal dependency on individual gatekeepers.
• Full‑stack responsibility: Engineers contribute across product development, infrastructure, and operations according to business needs.

You will continue to build product features alongside the broader engineering team, while taking a leading role in improving the platform and operational foundations that enable the entire organization to deliver software safely and efficiently.