17 hours ago
São Paulo, BrazilSenior
Responsibilities
- Own services end-to-end, including design, implementation, rollout, and production operation.
- Build backend services and data pipelines that generate, validate, score, version, and reproduce datasets.
- Develop performant internal interfaces with virtualized tables, server-side filtering, review workflows, and annotation UIs.
- Build agent harnesses with multi-step tool-use loops, retries, and structured outputs against real repositories and test suites.
- Create sandboxed execution environments for safe, deterministic, high-volume execution of model-generated code, along with RL environments and evaluation harnesses.
- Trace and debug agent runs, tool calls, graders, and end-to-end workflow failures.
- Own infrastructure as code and CI/CD, debug production issues across the stack, and drive reliability improvements.
- Contribute through code reviews and design documents while partnering with researchers and quality owners.
Requirements
- 6+ years of experience building and operating production software.
- Deep Python experience with FastAPI and/or Django, including ORM performance, migrations, and asynchronous patterns.
- Strong PostgreSQL skills covering schema design, query optimization, and indexing, plus NoSQL experience.
- Production experience with TypeScript, React, and Next.js.
- Fluency with Linux and Docker, Terraform or comparable infrastructure as code, AWS or GCP, and CI/CD ownership.
- Daily use of LLM coding tools such as Claude Code, Cursor, or Copilot, with the ability to critically review their output.
- Experience building dependable systems on top of LLM APIs, such as agents, pipelines, or evaluations.
- Ability to work with non-deterministic systems and distinguish regressions from noise through controlled experiments.
- Advanced Git skills and strong testing discipline covering unit, integration, negative, and edge cases.
- Clear written communication, independent execution, and willingness to challenge incorrect specifications.
- Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Machine Learning, AI, or a programming-heavy IT field is preferred, though demonstrated outcomes and equivalent experience are accepted.
- Preferred experience includes internal tools or developer platforms, LangGraph, MCP, OpenAI or Anthropic tool use, gVisor, Firecracker, seccomp, Temporal, Airflow, Prefect, Dagster, Kubernetes, SWE-bench, Terminal-Bench, evaluation frameworks, RLHF, or RLVR.
Benefits
- Work at the frontier of AI by helping leading AI labs improve advanced models through expert datasets, reinforcement learning environments, and benchmarks.
- Contribute to leading-edge AI research and potentially showcase work at conferences such as ICLR, ICML, and NeurIPS.
- Apply frontier AI innovations to enterprise business challenges.
- Collaborate with colleagues who have experience at Google, Meta, Amazon, and other leading technology companies.
- Work with startup-level ownership and pace in an AI-focused environment.
Tech Stack
Apache AirflowAWSDjangoDockerFastAPIGoogle Cloud PlatformKubernetesLinuxMongoDBNext.jsPostgreSQLPythonReactTerraformTypeScript
Categories
About Turing
Turing builds AI data pipelines and systems for enterprises and AI labs. It creates large-scale datasets and reinforcement-learning environments to train and evaluate models, and deploys agentic AI applications in domains like software engineering and enterprise workflows. The company also operates an AI-powered talent cloud to match and manage developers and AI trainers. Founded in 2018 and headquartered in San Francisco, it is privately held and serves Fortune 500 customers.