Our client is a leading online marketplace company, connecting millions of users and enabling people to buy and sell products and services across hundreds of categories. The company is currently transforming its technology platform and moving toward AI-native software development, with a strong focus on using AI agents to improve how software is designed, developed, tested, reviewed, and delivered.
We are looking for a Senior Software Engineer to build and operate agentic development workflows that transform the way software is delivered.
You will design pipelines in which AI agents help take product requirements through specification, implementation, testing, code review, and production-ready delivery, with human checkpoints where appropriate.
You will own these workflows from concept through production, monitor their performance, and continuously improve them based on their impact on engineering teams, product teams, and end users.
O que esta busca pede
Competências da vaga. Imprescindível é o que a posição precisa; diferencial soma, mas não substitui.
LLM · mínimo 4 anosCodex · mínimo 4 anosClaude Code · mínimo 4 anosCI/CD · mínimo 3 anosGCP · mínimo 3 anosAWS · mínimo 3 anosAI tools · mínimo 3 anosInglês · mínimo Avançado · imprescindível
O que a posição pede no dia a dia
- End-to-End Ownership:
- Identify opportunities, define problems, build solutions, deploy them, and continuously improve them after release.
- Agentic Development Pipelines:
- Design and operate workflows that take requirements from project management tools such as Jira or Linear through specification, implementation, testing, review, and delivery.
- Spec-Driven Development:
- Transform ambiguous product and engineering requests into clear specifications that can be effectively used by AI agents and automated workflows.
- Agent Orchestration:
- Coordinate long-running agent workflows using Temporal or comparable workflow engines.
- Handle retries, failures, state management, and human approval processes.
- Evaluation & Observability:
- Monitor and evaluate agent behavior, quality, latency, and cost using tools such as LangFuse or comparable platforms.
- Build evaluation frameworks, regression suites, guardrails, and quality gates.
- LLM Tooling:
- Integrate AI development tools such as Claude Code and Codex.
- Select models and tools according to the requirements of each task, considering cost, speed, and quality.
- Adoption & Continuous Improvement:
- Work closely with engineering teams to adopt new AI-assisted development workflows.
- Document effective practices and help teams incorporate them into their development processes.
- Review agent-generated code and continuously improve build and testing systems.
- Must-Haves:
- Senior-level software engineering experience, including building and operating production systems.
- Demonstrated experience building and improving agentic development workflows, beyond simply using AI tools for individual coding tasks.
- Ability to take ambiguous problems from initial concept through production monitoring with minimal direction.
- Strong product judgment, including the ability to define users and problems, make practical trade-offs, and measure outcomes.
- Hands-on experience transforming requirements into specifications that support automated implementation and validation.
- Strong engineering fundamentals in system design, testing, security, and failure handling.
- Nice-to-Have Skills:
- Experience building applications used directly by customers.
- Experience with large-scale marketplaces, e-commerce, or classifieds platforms.
- Backend experience with technologies such as:
- Java
- Python
- Spring
- Dropwizard
- MySQL
- MongoDB
- Microservices
- Frontend experience with:
- React
- Next.js
- Node.js
- GraphQL
- Backend-for-Frontend (BFF) architectures
- Mobile development experience with Flutter and Dart.
- Cloud experience with Google Cloud serverless services, particularly:
- Cloud Run
- Cloud Armor
- Pub/Sub
- Firestore
- Strong communication skills and the ability to help other engineers adopt new development practices.
- Core Requirements:
- Experience with agent and workflow orchestration using Temporal or a comparable workflow engine.
- Experience with LLM observability and evaluation, using LangFuse or similar tools.
- Daily experience with AI development tools such as Claude Code and Codex.
- Experience building evaluations, regression tests, guardrails, and quality gates for AI-generated work.
- Understanding of prompt engineering, context engineering, tool use, MCP servers, and model selection/routing.
- Familiarity with CI/CD, such as GitHub Actions.
- Experience with cloud platforms such as GCP or AWS.
- Ability to work across unfamiliar programming languages, systems, and codebases.
- No specific programming language is required.