Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading digital bank in Latin America serves more than 135 million customers across Brazil, Mexico, and Colombia. The organization has helped transform the financial services industry by leveraging data and proprietary technology to develop innovative products and services.
Key Responsibilities
Applied AI & Agentic Systems
- Design, build, and deploy LLM-powered agents and workflows that automate complex internal processes from end to end.
- Work hands-on with frontier models and modern AI technologies, including tool and function calling, structured outputs, MCP, RAG, and multi-agent orchestration.
- Own the complete lifecycle of AI systems, from problem discovery and prototyping through production hardening, monitoring, and continuous iteration.
Evaluation & Reliability
- Build evaluation harnesses, guardrails, and quality feedback loops that enable AI systems to operate reliably in production.
- Define measurable standards for non-deterministic AI systems and implement evaluations, regression suites, and human-in-the-loop reviews where appropriate.
- Identify, monitor, and address AI failure modes to continuously improve system quality and reliability.
Intelligent Workflow Automation
- Use orchestration platforms such as n8n and custom integrations to deliver AI-assisted automation across business units.
- Integrate enterprise platforms such as Slack, Google Workspace, Jira, and internal APIs into cohesive AI-assisted workflows.
- Identify manual and inefficient business processes where AI can provide measurable improvements.
AI Adoption & Governance
- Drive the technical strategy for AI adoption across engineering and business workflows.
- Develop governance frameworks that make AI coding assistants and agents safe, compliant, and effective.
- Balance developer flexibility with security, privacy, operational, and compliance requirements.
Multiplier Work
- Create Golden Paths, reference implementations, and documentation that enable other teams to safely develop and deploy AI workflows.
- Serve as a technical reference for applied AI within the domain and influence architecture beyond the immediate team.
- Mentor senior and mid-level engineers and promote responsible AI engineering practices.
- Partner with security and privacy teams to ensure AI solutions align with organizational policies.
Required Qualifications
- Demonstrated experience shipping LLM-powered systems into production, including agents, copilots, RAG applications, or AI-driven automations used by real users.
- Hands-on experience with prompt engineering, context engineering, tool and function calling, structured outputs, and agent frameworks or orchestration patterns.
- Experience measuring and improving AI output quality through evaluations, test sets, feedback loops, and quality monitoring.
- Strong understanding of AI failure modes, including hallucinations, model drift, and prompt injection.
- Strong software engineering fundamentals with proficiency in Python, TypeScript, or Clojure.
- Strong API development and integration skills.
- Experience building maintainable production systems rather than relying primarily on notebooks or prototypes.
- Strong AI product judgment, including the ability to determine which problems are appropriate for LLMs, deterministic automation, or no automation.
Disclaimer
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