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 (LatAm)

Type: Full-time

Working hours: Must be willing to work Pacific Time (PT) business hours. Brazil is ~4⁄5 hours ahead of PT and Colombia ~2⁄3 hours ahead; comfortable overlap with a Pacific-based team is required.

Role Overview

We are looking for a Senior Engineering Manager who is, first and foremost, a hands-on technical leader. You will lead a small team building custom AI and data solutions for enterprise clients, and you will stay deep in the work: operating on data, organizing the technical stack, setting up infrastructure, and personally delivering when a project is on the line.

This role blends real engineering skill with people and project leadership. If a project has to ship and you are the person available to ship it, you are able to do so end to end. We operate like a rapid-iteration startup: schedules are urgent, expectations are high, and the people who thrive here are excited by that pace.

What We’re Looking For

The three qualities that matter most for this role:

Ownership and drive. You take on more than your role strictly requires. You are prolific, high-energy, and responsive when the business needs you. You treat delivery deadlines as your own and prioritize the urgent, important work on your schedule.
Technical competence. You are genuinely hands-on. You can code yourself, operate the data, organize the technical stack, and set up infrastructure. You guide the team on architecture, design, and implementation, and you can step in and build when it counts.
People and organizational leadership. You run tight, well-organized engineering execution: clear technical specs, well-scoped tasks, and consistent on-time (or ahead-of-time) delivery. You have led teams through urgent, high-stakes schedules and delivered.

Key Responsibilities

Hands-on delivery and technical leadership

Own end-to-end project delivery, stepping in personally to build, operate data, configure the stack, or set up infrastructure whenever needed.
Guide the team on architecture, design, and implementation of scalable, maintainable solutions.
Run precise engineering planning: define technical specs, scope tasks clearly, and drive execution to consistent on-time delivery.

Team and workstream management

Lead and organize a team building custom AI/data solutions for enterprise clients.
Allocate work across the team based on skills and performance, and prioritize to meet business goals.
Coordinate with cross-functional partners to keep projects aligned.

Throughput, quality, and iteration

Monitor progress and optimize development processes for speed and efficiency in a fast, iterative environment.
Perform spot reviews on tasks, give actionable feedback, and catch risks early.
Ensure work meets quality standards before it ships.

Talent and performance

Identify high and low performers through reviews and metrics; mentor, develop, and manage talent accordingly.
Build up team members and support their growth toward more advanced work.

Qualifications

Proven track record of leading teams, especially in startup or fast-moving, project-based environments, delivering complex technical work under tight deadlines. This is the primary filter.
Hands-on technical strength — expert-level, current engineering ability (e.g., Python and JavaScript ecosystems), with the ability to personally deliver.
Data fluency — proficiency with data analysis and data quality practices (statistical analysis, data manipulation, and tools such as Pandas, NumPy, and SQL), and the ability to lead data validation, cleansing, and enrichment.
7+ years in software engineering, with at least 2 years leading a team (typically 5-6+ people).
Bachelor’s or Master’s in Computer Science, Engineering, or a related field. Backgrounds in AI, data science, or data engineering are strongly preferred;
AI or fine-tuning / custom-data experience is a plus but not required — diligence, track record, and ownership come first.
Excellent communication and the ability to collaborate across cross-functional teams.

What Success Looks Like

You are the kind of leader who is excited to do this work. You know it will be intense, that you’ll manage a lot of people, process, and technology at once, and you welcome it. You have taken on something genuinely hard, led people through it, and can clearly explain what made it difficult and how you delivered — a truly hard technical milestone, reached in a leadership setting, that you’re proud of.

Values

We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value.
We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection
We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.

Advantages of joining Turing

Work at the frontier of AI, helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks.
Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS.
Bring frontier AI innovation to the enterprise, applying lessons learned from leading AI labs to solve real-world business challenges.
Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies.
Move at the pace of AI innovation, with the speed, ownership, and impact of a startup.

Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

For applicants from the European Union, please review Turing’s GDPR notice here.

Career Guide for Senior Engineering Manager, AI at Turing

Job Overview

The Senior Engineering Manager at Turing is a leadership role focused on delivering custom AI and data solutions for enterprise clients. This position combines hands-on technical expertise with effective team management, requiring an individual who is comfortable coding and building solutions. The ideal candidate should thrive in a fast-paced environment where deadlines are critical, and innovation is key.

Key Responsibilities

Project Delivery: Own the end-to-end process of delivering AI solutions, stepping in personally as needed.
Technical Leadership: Guide the team in architecture, design, and implementation, ensuring scalable and maintainable solutions.
Team Management: Lead a dedicated team, allocating work based on skills, and collaborating with other departments to maintain project alignment.
Process Optimization: Monitor development processes to improve speed and efficiency, providing feedback and catching risks early.
Talent Development: Identify team strengths and weaknesses, mentoring staff to foster growth and improve performance.

Required Skills and Knowledge

Technical Skills

Expertise in programming languages such as Python and JavaScript.
Proficiency in data analysis tools, including but not limited to Pandas, NumPy, and SQL.
Familiarity with AI, data science, or data engineering concepts.

Soft Skills

Strong leadership and organizational abilities.
Excellent communication skills for cross-functional collaboration.
Problem-solving mindset with a proactive approach to project challenges.

Tools and Technologies

Software development environments and tools related to AI and data solutions.
Project management software for scheduling and team coordination.

Certifications or Training

A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field is preferred.
Courses or certifications in AI, data analysis, or project management can enhance hiring prospects.

Interview Preparation

10 Common Interview Questions

Can you describe your experience leading teams in a fast-paced environment?
- Focus on specific examples that highlight your leadership style and successes.
How do you prioritize tasks in a high-pressure situation?
- Discuss your approach to urgent requests and time management strategies.
What is your experience with coding and hands-on engineering work?
- Provide details on your technical abilities and how you’ve applied them in projects.
Describe a challenging technical problem you solved.
- Use the STAR method (Situation, Task, Action, Result) to structure your response.
How do you handle conflicts within your team?
- Share examples of conflict resolution and maintaining team morale.
What tools do you use for data analysis and why?
- Explain your preferred tools and their benefits in software engineering projects.
Can you give an example of a project that was delivered ahead of schedule?
- Highlight your planning and execution strategies that led to this success.
How do you ensure quality standards are met in your team’s work?
- Discuss your monitoring and review processes.
What is your experience with mentoring team members?
- Share your approach to talent development and support for colleagues.
Why are you interested in working with AI and at Turing specifically?
- Display your passion for AI and how it aligns with Turing’s mission.

Important Topics to Review

Leadership in software engineering.
AI and data science fundamentals.
Client-oriented project management.
Effective communication strategies.

How to Increase Your Hiring Chances

CV Improvement

Tailor your CV to highlight relevant experience in leading software projects and teams.
Use metrics to demonstrate your impact, such as project delivery times or team performance improvements.

LinkedIn Profile Optimization

Update your profile to reflect your most recent experiences and skills.
Engage with AI and tech communities by sharing articles or writing insights related to the field.

Portfolio or Project Ideas

Work on personal or open-source projects that showcase your AI and data skills.
Contribute to community forums or write technical blogs to demonstrate expertise.

Learning Recommendations

Attend workshops or online courses focused on AI and data engineering.
Stay updated with the latest trends and advancements in AI through reputable resources and publications.

Career Growth

Short-Term: Move from Senior Engineering Manager to Director of Engineering or a similar role, overseeing multiple teams.
Mid-Term: Transition into a higher executive position like VP of Engineering or Chief Technology Officer, focusing on strategic direction.
Long-Term: Opportunities for consulting or starting your own AI-focused business, leveraging your expertise and industry connections.

By following this career guide, candidates can effectively prepare for the Senior Engineering Manager position at Turing and increase their chances of securing the role, while also planning for future advancements in their careers.