Senior Engineering Manager

About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com .    Senior Engineering Manager, AI (Technical Team Lead) Location: Remote, Brazil or Colombia Status: Full time  Role Overview As a Senior Engineering Manager (Technical Team Lead) at Turing, you will be a pivotal part of our engineering leadership for AI initiatives. This is not a pure people management role. You will be expected to be hands on: able to operate on the data, organize the stack, set up infrastructure, and personally deliver a project if no one else is available. You will lead a team through a rapid iteration, startup paced environment with high expectations and short timelines, while also driving the technical vision and execution of complex projects. The ideal candidate is someone who takes ownership beyond what their role technically requires, has a track record of delivering under pressure, and is excited by the intensity of a startup environment rather than looking for a more comfortable, longer timescale management track. Key Responsibilities Hands On Technical Ownership: Operate directly on data, organize the technical stack, and set up infrastructure as needed. Be the technical fallback who can personally deliver a project if no one else is online to do it. Guide the team in architecture, design, and implementation of scalable, maintainable codebases. Build and use AI agents, and review the team's agent based work, since this role requires evaluating agent output directly rather than only reviewing human written code. Prompt Generation and Innovation: Lead innovation efforts in product features and processes. Manage idea and prompt collection and prioritization. Drive experimentation and iteration for optimal outcomes. Work Stream Assignment Across Pods: Allocate projects based on skills and performance. Prioritize tasks to meet business goals. Coordinate with cross functional teams for project alignment. Team Throughput and Task Completion: Monitor progress using metrics like velocity and cycle time. Optimize development processes for efficiency. Ensure tasks meet quality standards before deployment. Spot Reviews on Tasks: Perform quality control through task reviews. Provide actionable feedback to maintain high standards. Identify risks early and adjust processes accordingly. Identifying High and Low Performers: Conduct performance analysis through reviews and metrics. Provide mentorship, feedback, and talent management. Identify high performers for advanced roles and support development for others. People and Project Leadership Under Pressure: Lead teams through urgent, high pressure delivery schedules, not just steady state work. Push delivery timelines in a rapid iteration startup context while maintaining quality. Take direct ownership of outcomes, including being responsive when urgent needs arise. Technical Skills Expert level, hands on experience in Node.js, with React and NestJS specifically, including a deep understanding of their ecosystems, libraries, and best practices. Experience with Infrastructure as Code (IaC) and GCP, including setting up and operating cloud infrastructure directly. Ability to build and use AI agents, with enough fluency to review and evaluate a team's agent built work. Experience leading projects that leverage Python for data analysis, backend development, or AI and ML applications, as well as JavaScript and TypeScript for front end and full stack development. Proficiency in data analysis techniques, including statistical analysis, data visualization, and data manipulation using tools like Pandas, NumPy, and SQL. Strong focus on data quality, including data validation, cleansing, and enrichment. Qualifications Bachelor's or Master's degree in Computer Science, AI, Data Science, Data Engineering, or a related field. Electrical engineering backgrounds are acceptable. AI or data science background is a meaningful plus (helps significantly) but not a dealbreaker if diligence and ownership are evident elsewhere. 7+ years of experience in software de