Descripción del puesto

You'll build and ship software across the full stack as an adaptive generalist, using AI tools as a force multiplier to move into unfamiliar territory and solve problems that would otherwise sit outside your comfort zone. Rather than specializing narrowly, you will be expected to learn fast, pick up new languages, frameworks and domains as the work demands, and use AI to compress the distance between "I haven't done this before" and "it's done and it works."

The Impact You'll Have

• On the delivery team: absorb work wherever it appears ( frontend, backend, data, infra, glue) without waiting for the "right" specialist, keeping the team unblocked and velocity high.
• On the DEV Department: model what AI-augmented engineering looks like in practice, spread effective tooling and workflows to peers, and raise the floor on how much one developer can credibly own.
• On our customers: deliver working software quickly and adapt as requirements shift, covering more ground per engineer while keeping quality intact.

What You'll Do

Generalist delivery (the fundamentals)

• Build, test, and ship features across the stack (frontend, backend, APIs, data, and the integration glue between them) without being boxed into a single layer.
• Move fluidly between coding languages, frameworks, and domains, picking up whatever the task requires rather than waiting to be handed work that matches an existing specialty.
• Own work end to end: from understanding the problem, through implementation and testing, to deployment and follow-up.
• Write code that other people (and AI tools) can read, maintain, and extend — clear structure, sensible naming, and tests where they matter.

AI-augmented problem solving

• Use AI coding assistants and agents (code generation, refactoring, test writing, *debugging, code review) as a daily part of your workflow — not as a novelty, but as a core tool.
• Reach past your personal boundaries deliberately: take on tasks in unfamiliar stacks or domains and use AI to ramp up quickly, validate the output, and ship with confidence.
• Treat AI output critically — verify, test, and understand generated code rather than pasting it blindly; know when the tool is wrong and when to override it.
• Use AI to accelerate the unglamorous parts of the job too: understanding legacy code, writing documentation, drafting tests, exploring an unfamiliar API, or scaffolding a prototype.
• Continuously refine your personal and team workflows: prompts, context setup, tooling, and the judgment of when AI helps versus when it gets in the way.

Adaptability & learning

• Learn new technologies on the job, fast — treat unfamiliarity as a normal starting condition rather than a blocker.
• Adjust quickly to shifting requirements, priorities, and contexts without losing momentum.
• Bring a problem-solving mindset over a tool-specific one: start from the outcome the work needs and find the path to it, AI-assisted or otherwise.
• Stay current with a fast-moving AI tooling landscape and fold useful new capabilities into your daily practice.

Collaboration & enablement

• Share working AI workflows, prompts, and tooling tips with the team so the whole group gets faster, not just one person — in the spirit of our "ideas worth spreading" culture.
• Communicate clearly in English with teammates and customers; explain decisions and trade-offs simply.
• Collaborate across roles — pair with specialists when depth is needed, and hand off cleanly.
• Give and receive code review constructively, including review of AI-generated changes.

Requisitos

Experience

• Solid senior-level software development experience across more than one part of the stack (e.g., both frontend and backend, or backend and data/infra). Demonstrated breadth and a track record of shipping matter most.
• Proven track record of picking up new technologies quickly and delivering in them.
• Hands-on, regular matured use of AI coding tools as part of real delivery work (not just experimentation).

Technical knowledge

• Strong programming fundamentals: data structures, algorithms, and clean code principles that transfer across languages.
• Comfort across at least two layers of the stack and a clear willingness to operate outside any single specialty.
• Working knowledge of version control, testing, debugging, CI/CD, and basic cloud/deployment concepts.
• Practical command of AI-augmented development: prompting, providing good context, validating output, and integrating AI tools into the workflow.

Skills & mindset

• Adaptive and curious — genuinely energized by unfamiliar problems rather than deterred by them.
• Strong, independent problem-solving ability paired with the judgment to know when to ask for help.
• Professional communication in English, written and spoken.
• Critical thinking about AI output — healthy skepticism, not blind trust.
• Self-driven, with the ownership to take something from ambiguous to done.

Nice to Have

• Experience shipping across many distinct domains (web, mobile, data, infra, integrations).
• Familiarity with multiple AI coding tools and agentic dev environments, and a point of view on their trade-offs.
• Experience prototyping quickly to validate ideas before committing to a full build.
• Contributions to team practices, internal tooling, or knowledge-sharing around AI-augmented development.
• Exposure to customer-facing or pre-sales/discovery work.

Beneficios

English lessons.
EAP Program