AI-native Senior Backend Software Engineer

AI-native Senior Backend Software Engineer

OLX Group

Remote, Portugal

Who we are looking for:

• You use agentic workflows (Claude Code, Cursor Agent, or equivalent) as your default, not as a novelty; you understand model routing trade-offs (e.g., when to use Haiku vs. Sonnet vs. Opus) and multi-agent orchestration.
• You practice context engineering, not just prompt engineering; you design the full information architecture an AI agent needs to succeed: repo structure, CLAUDE.md/AGENTS.md configs, relevant code context, memory, and tool access.
• You have strong CS fundamentals and hands-on technical depth in Golang, Java (Kotlin) (preferred technologies), able to work with PHP; you spend the majority of your time designing solutions, steering and reviewing AI-generated code, and contributing to a large-scale codebase.
• You have scalable systems expertise: experience with large-scale web applications, well-bounded domain design, AWS cloud architecture, IaC (Terraform, CloudFormation), and solid database fluency (MySQL, DynamoDB, Redis, Memcached).
• You are a product-minded engineer: you challenge decisions with a cost/value lens, articulate how services should evolve to meet business goals, and communicate clearly in English across engineering and product audiences.
• You live "you build it, you run it, you own it." AI output is a first draft, not a deliverable. You validate, refactor, take full accountability, and proactively identify what needs to be done without waiting to be asked.

What you will be doing:

• Apply context pipeline discipline within your team's codebase: scope context windows to repo boundaries, domain knowledge, test outputs, and CI feedback so agents consistently produce reliable, mergeable code on real team work items.
• Write agent-actionable task specifications for your team's backlog (clear acceptance criteria, referenced modules, explicit constraints) and keep the codebase agent-ready: well-bounded repos, comprehensive test suites as guardrails, and CI/CD pipelines with structured output agents can parse and act on.
• Lead delivery of complex initiatives: break them into incremental milestones, manage cross-team dependencies, navigate ambiguity, and make deliberate quality-vs-delivery trade-offs, ensuring timely delivery without sacrificing standards.
• Mentor engineers and contribute to the AI Champion community: share effective agentic workflows, run workshops, and help the team adopt AI-assisted practices.
• Uphold standards for GraphQL API design, RESTful contracts, database schema, and CI/CD quality; lead incident response for your team; and manage technical debt with AI as an accelerator, not a shortcut.