Degree in Computer Science/Engineering, or equivalent experience
5+ years of relevant professional experience in a data engineering role, with experience leading technical workstreams, mentoring junior engineers, and driving the adoption of software engineering best practices within a team
Expert-level proficiency in Python and SQL and the ability to work in polyglot environments (Scala, Java) when required by client enterprise systems
Strong experience building Agentic AI, Generative AI, Machine Learning, and Business Intelligence systems, including prompt design, retrieval-augmented generation (RAG), embeddings, vector databases, context construction, and output handling in production workflows using modern frameworks (Spark, LangChain, Databricks, Dask, Airflow, Dagster, Kedro, etc.)
Ability to lead the implementation of AI features end to end, with sound judgment around model behavior, evaluation, reliability, guardrails, and the trade-offs between quality, latency, and cost
Experience implementing robust data security and governance controls, including managing PII/PHI, authentication, and role-based access control (RBAC)
Deep knowledge of MLOps/LLMOps including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse), and infrastructure as code (Terraform) across cloud providers (AWS, Azure, GCP)
Exceptional time management and ability to own technical workstreams autonomously
Experience using coding agents (Cursor, Claude Code, Codex, etc.) is a plus
Strong communication skills, both verbal and written, in English and Portuguese