AI Engineer collaborating with AI recruiters Alex and Mila to connect candidates to suitable job opportunities. Handling important communication and application processes effectively.
About the role
- DCoder Lead at dLocal, overseeing technical vision for AI-assisted coding platform. Collaborating across teams to enhance developer experience and ensure robust AI integration.
Responsibilities
- Own the architecture, roadmap, and evolution of DCoder, integrating with LLMs, CI/CD, repos, and engineering workflows.
- Drive developer adoption through documentation, demos, training, and enablement materials.
- Define best practices and guardrails for AI-assisted coding (prompt design, context management, evaluation, safety).
- Partner with Engineering, Platform, Security, and Product to align priorities and deliver impact.
- Ensure DCoder operates reliably at scale — balancing performance, cost, security, and usability.
- Gather continuous feedback from developers and iterate quickly on improvements.
- Establish governance and standards around responsible AI usage in SDLC workflows.
Requirements
- Real software development experience: 5+ years hands-on engineering, having shipped and operated production code; fluency with Git, code review, CI/testing, and modern backend/front-end stacks.
- Proven experience applying AI and LLM-based systems in real-world environments, including assistants and agents used at scale.
- Solid understanding of AI system technology (LLMs, APIs, orchestration, prompt/context management, evaluation, cloud platforms).
- Practical knowledge in building and deploying microservices and integrating third-party APIs and AI services.
- Experience with monitoring applications in production.
- Hands-on experience with AWS; GCP is a plus.
- Product management or equivalent ownership experience, preferably in developer tools, platforms, AI/ML systems, or infrastructure.
- Experience leading and developing engineers, providing technical direction, prioritization, and support while fostering high standards and autonomy.
- Ability to read/reference code and architecture, prototype to de-risk ideas, and define clear success criteria.
- Comfortable designing metrics, running experiments, and using telemetry to inform prioritization and validate changes.
- Strong ability to work in close partnership with Product, contributing to discovery and prioritization.
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