Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Manager, AI Data Engineering (UK Remote)

Turnitin
Newcastle upon Tyne
3 days ago
Create job alert
Overview

Turnitin is an AI-focused leader in the educational and research sectors, promoting academic integrity and innovation for over two decades. We are renowned for our cutting-edge solutions used by thousands of academic institutions, corporations, and publishers worldwide.

Turnitin offers remote working as a standard arrangement and is a remote-first employer with an office in Newcastle (UK) and colleagues spanning the globe. We value flexibility, diversity, local cultures, and individual choices, all aimed at making a significant impact in education.

AI and data science are integral to our success and ambitious product roadmap. Joining us as an AI Data Engineer means becoming part of a global team of proactive, supportive, and independent professionals delivering sophisticated, well-structured AI and data systems. You will help pioneer our next generation data and AI pipelines, collaborating with different teams within Turnitin to integrate AI and data science across a broad suite of products that enhance learning, teaching, and academic integrity.

Responsibilities

In your role as AI Data Engineering and Data Science Manager, you’ll lead a team that owns all data collection and data curation for the AI team, with emphasis on automated data collection and labeling using state-of-the-art AI and LLMs. Key responsibilities include:

  • Leadership: Build and grow a team of AI data engineers, ensuring their growth and high performance.
  • Strategy: Advise senior leadership on how to leverage AI-driven data engineering to create future-ready data and AI strategies.
  • Communication: Ensure clarity of the company’s vision and mission across the team and foster excellent communication within the organization.
  • AI Data Engineering: Design, build, operate and deploy real-time data pipelines at scale using AI methods and best practices. Apply cutting-edge data warehousing, data science and data engineering technologies to accelerate Turnitin’s AI R&D efforts. Identify strategic unlocks such as LLM agents to enable faster time-to-market and better reusability of AI initiatives.
  • Collaboration: Partner cross-functionally with teams across Turnitin, especially AI R&D, Applied AI, and Data Platform teams, to collect, create, curate and catalog high-quality AI datasets that drive our AI pipeline and answer critical business questions. Ensure alignment and integration of data architecture and data models across products and platforms.
  • Hands-on Involvement: Engage in data engineering and data science tasks as required to support the team. Lead external data collection efforts, including state-of-the-art prompt engineering techniques, to support the construction of state-of-the-art AI models.
  • Innovation: Drive data innovation through research and development to extract insights from Turnitin’s data resources.
  • Continuous Learning: Stay updated on new tools and development strategies and bring innovation recommendations to leadership.
Qualifications

Required Qualifications;

  • At least 5 years of experience in data engineering and data science, ideally focused on enabling and accelerating AI R&D.
  • At least 2 years of experience in a managerial or technical leadership role, with responsibility for large cross-functional projects.
  • Strong proficiency in Python, SQL, and Infrastructure as Code (Terraform, CloudFormation), with experience in modern orchestration frameworks (Airflow, Prefect, or dbt).
  • Proficiency with cloud-native data platforms (AWS, Azure, GCP) and vector databases (Pinecone, Weaviate, Qdrant, or Chroma).
  • Experience with MLOps tools and platforms (HuggingFace, SageMaker Bedrock, Vertex AI), experiment tracking (MLflow, Weights & Biases), and model deployment pipelines.
  • Experience with Large Language Models (LLMs), embedding generation, retrieval-augmented generation (RAG) systems, and frameworks for orchestrating LLM interaction (LiteLLM, LangFuse, LangChain, LlamaIndex).
  • Strong problem-solving, analytical, and communication skills, with the ability to design scalable AI data systems and collaborate effectively in cross-functional teams.

Desired Qualifications:

  • 7+ years of experience in data engineering and data science, with a focus on AI and machine learning projects.
  • 2+ years of experience in a managerial or technical leadership role.
  • Experience in education, EdTech, or academic integrity sectors.
  • Experience using AI coding tools (Cursor, Claude Code, GitHub Copilot) for accelerated development.
  • Familiarity with natural language processing, computer vision, or multimodal AI applications.
  • Experience with data visualization (Streamlit) and data reporting.
Characteristics for Success

As an AI Data Engineering and Data Science Manager, you should have:

  • A passion for creatively solving complex data problems.
  • Ability to work collaboratively and cross-functionally, with strong leadership skills.
  • A strong growth mindset and ability to constantly improve your skills and knowledge.
  • Excellent track record of delivering results and ensuring a high level of quality.
  • A desire to mentor, guide and grow high potential individual contributors.
  • Excellent written and verbal communication skills.
  • A sense of curiosity about the problems at hand, the field at large, and the best solutions.
  • Strong system-level problem-solving skills.
Additional Information

Total Rewards @ Turnitin
Turnitin maintains a Total Rewards package that is competitive within the local job market. This includes monetary and non-monetary rewards, generous time off and health and wellness programs that prioritize well-being and flexibility. The company emphasizes a remote-centric culture and a comprehensive package to support employees.

Our Mission is to ensure the integrity of global education and meaningfully improve learning outcomes.

Our Values underpin everything we do.

  • Customer Centric - Put educators and learners at the center of everything we do to ensure integrity and improve learning outcomes.
  • Passion for Learning - Encourage constant learning and growth and provide a workplace that enables it.
  • Integrity - The heartbeat of Turnitin, shaping our products and interactions.
  • Action & Ownership - Bias toward action and empowerment to make decisions.
  • One Team - Break down silos, collaborate effectively, and celebrate successes.
  • Global Mindset - Respect local cultures and embrace diversity to maximize impact.
Global Benefits
  • Remote First Culture
  • Health Care Coverage*
  • Education Reimbursement*
  • Competitive Paid Time Off
  • 4 Self-Care Days per year
  • National Holidays*
  • 2 Founder Days + Juneteenth Observed
  • Paid Volunteer Time*
  • Charitable contribution match*
  • Monthly Wellness or Home Office Reimbursement/*
  • Access to Modern Health (mental health platform)
  • Parental Leave*
  • Retirement Plan with match/contribution*

* varies by country

Seeing Beyond the Job Ad

At Turnitin, we recognize it’s unrealistic for candidates to fulfill 100% of the criteria in a job ad. We encourage you to apply if you meet the majority of the requirements because we know that skills evolve over time. If you’re willing to learn and evolve alongside us, join our team!

Turnitin, LLC is committed to the policy that all persons have equal access to its programs, facilities and employment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.


#J-18808-Ljbffr

Related Jobs

View all jobs

Manager, AI Data Engineering (UK Remote)

Manager, AI Data Engineering (UK Remote)

Manager, AI Data Engineering (UK Remote)

Data Engineering Manager, London

Assurance - Financial Services - Forensic Data Analytics - Senior Manager - London

Assurance - Financial Services - Forensic Data Analytics - Senior Manager - London

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.