Jobs at Turing

Lead discovery with stakeholders to map workflows and controls, write clear problem statements and delivery-ready requirements (user stories, acceptance criteria), partner with product and engineering, support UAT and testing, maintain traceability and auditability, and use AI tools responsibly to accelerate analysis and documentation.

Lead discovery and delivery of AI-enabled back-office finance solutions. Define roadmap, translate workflows into epics/stories, coordinate engineering and data science, manage stakeholders, prioritize backlog, ensure controls, and run disciplined execution for reconciliation, NAV, GL, and operational controls.

The AI Engineering Lead at Turing will lead a team to deliver Generative AI solutions, building technical roadmaps, designing architectures, and ensuring execution to meet client needs.

Lead end-to-end multimodal AI programs as the primary client-facing delivery owner. Design scalable annotation, evaluation, and RLHF pipelines across vision, image/video generation, and audio; define quality systems and rubrics; build and manage cross-functional delivery teams; translate model requirements into program plans; track milestones, risks, and metrics; and drive account growth and operational playbooks for US clients while working LATAM hours.

The Research Engineer role involves building and improving deep learning systems, focusing on data quality, dataset and RL environment design, and collaborating with researchers to meet high standards for AI applications.

The Research Engineer will design datasets and RL environments, ensuring high data quality for AI systems development, and collaborate with teams to evaluate outcomes.

The Client Director will lead large-scale LLM training programs, managing global teams, ensuring data quality, and overseeing client relationships. Responsibilities include optimizing workflows, developing automation tools, and enhancing model performance through high-quality datasets.

The Forward Deployed Engineer will design, build, and deploy GenAI applications for customers, collaborating with various teams and ensuring robust solutions using Python and cloud platforms.

Develop and optimize LLM-based solutions, maintain code in Python and SQL, integrate with cloud services, and provide mentoring. Collaborate cross-functionally and innovate in generative AI techniques.

The Staff Research Engineer - Code will lead the creation of datasets and reinforcement learning environments for coding agents, collaborating with AI labs to influence model improvements and operational excellence, while managing a technical team.

This role involves building and deploying AI/ML models, leading engineering teams, ensuring timely execution of projects, and continuously innovating in generative AI and LLM applications.

Lead and optimize Talent Operations processes at scale, manage KPIs and a 15+ person team, drive AI-forward automation, improve candidate experience, own stakeholder reporting, and execute cost and process optimization initiatives.

Partner with the Head of Talent Growth to define and execute supply and demand growth roadmaps. Lead cross-functional growth programs, run experiments, optimize funnels and automation, build dashboards and metrics, and drive alignment across Product, Engineering, Data Science, and Sales to hit growth OKRs.

Own community strategy and execution for developer (supply) and customer (demand) audiences. Manage social channels, virtual and in-person events, partnerships, ambassador programs, and cross-functional alignment. Track community KPIs and deliver monthly performance briefings to drive engagement, retention, and top-of-funnel impact.

Lead and deliver GenAI projects: design and architect multi-agent LLM systems, build training/fine-tuning and deployment pipelines (RAG), own technical roadmaps, mentor engineers, implement evaluation and observability pipelines, and integrate solutions on cloud platforms to meet enterprise requirements.

Provide high-trust executive and personal support to the Founder & CEO: manage a complex, rapidly changing calendar; coordinate domestic and international multi-leg travel; handle personal, household, and family-office logistics; anticipate needs, solve problems proactively, and maintain confidential systems for files, contacts, and expenses. Partner closely with the Office of the CEO and internal/external stakeholders to preserve the CEO's time and priorities.

Support the CEO as an external force multiplier: run capital formation processes, craft investor/partner decks and memos, drive strategic partnerships with frontier labs and enterprises, build executive relationship systems, and lead high-impact confidential projects requiring judgment, discretion, and flawless execution.

Lead end-to-end program management for AI/LLM training and dataset creation: define scope, milestones, KPIs; coordinate data, engineering, annotation, QA, and vendors; ensure data quality and scalable processes; manage risks, reporting, client engagement, and tool integrations to deliver programs on time and within scope.

Lead design, development, fine-tuning, and deployment of LLM-based GenAI solutions (RAG, agents, prompt engineering). Own technical roadmaps, drive engineering delivery, mentor teams, integrate cloud deployments (Azure/GCP/AWS), maintain Python/SQL codebases (LangChain/LangGraph), and collaborate with product, data science, and business stakeholders.

The Forward Deployed AI Engineer designs, builds, and deploys intelligent applications using Python and related technologies, addressing customer needs and leading deployment projects.