About the Role
Innodata partners with industry-leading clients to help them scale their AI development and improve the experience of their customers. We are seeking an Engagement Manager to lead a team of Prompt Engineers who will help automate data annotation and human evaluation workflows through the use of Large Language Models (LLMs).
As the Engagement Manager, you will play a pivotal role in ensuring seamless communication between our client and the internal team. You’ll help drive project goals, coordinate tasks, and guide the execution of strategies to solve complex data labeling challenges, while overseeing the team’s day-to-day operations and technical progress.
You will be instrumental in fostering the direction of projects, ensuring your team delivers on set goals, and collaborating with the customer to ensure alignment on objectives.

Key Responsibilities

• Act as the primary point of contact between our client, their stakeholders, and Innodata internal teams, ensuring smooth collaboration and effective communication.
• Work directly with our customer and their stakeholders to define problem statements, refine project goals, and determine the best path forward for automation.
• Craft detailed project plans, set clear milestones, and ensure that the team delivers timely results, keeping all stakeholders informed and aligned.
• Guide the team in the technical execution of the project, ensuring the approach is scalable and aligned with the overall objectives.
• Ensure the generated results meet accuracy benchmarks, as measured against the gold standard.
• Collaborate with the team to continuously improve processes, based on feedback and performance metrics.
• Report on project status and results, providing actionable insights to both technical and non-technical stakeholders.

Required Skills and Experience

• A solid understanding of Large Language Models (LLMs) and prompt engineering.
• Proven experience in managing technical teams, ideally in AI, machine learning, or similar fields.
• Strong communication skills, with the ability to bridge the gap between technical and non-technical stakeholders.
• Ability to think strategically, anticipate challenges, and proactively drive project success.
• Experience in business analysis and project management, with an understanding of both technical and business needs.
• Ability to manage multiple priorities and drive results under tight deadlines.
• Strong writing and communication skills.
• Appreciation for issues of diversity, equity, and inclusion in AI systems and data annotation practices.

Preferred Skills and Experience

• Minimum of 2 years of hands-on experience managing technical projects.
• Experience in AI/ML project management, especially related to automation and data labeling.
• Familiarity with AI platforms and APIs, such as OpenAI, Hugging Face, and similar tools used for working with LLMs.
• Knowledge of data annotation workflows and the challenges associated with scaling human-in-the-loop systems.
• Prior experience working directly with clients, particularly in a constructive of advisory role.
• Familiarity with containerization and model deployment.
• Experience in using tools such as TensorFlow, PyTorch, and other relevant AI/ML tools in NLU contexts.

Minimum Education Requirements
Bachelor’s degree in Computer Science, Engineering, Data Science, Project Management, or a related field (or equivalent work experience).
Salary rates at Innodata vary depending on a wide array of factors, which may include but are not limited to the role, skill set, educational background and geographic location.
We are an equal opportunity employer committed to fostering an inclusive, respectful, and diverse workplace. We welcome and encourage applications from individuals of all backgrounds and are dedicated to employment equity and building a team that reflects the diverse communities in which we live and operate.

LI-NS1

• Act as the primary point of contact between our client, their stakeholders, and Innodata internal teams, ensuring smooth collaboration and effective communication.
• Work directly with our customer and their stakeholders to define problem statements, refine project goals, and determine the best path forward for automation.
• Craft detailed project plans, set clear milestones, and ensure that the team delivers timely results, keeping all stakeholders informed and aligned.
• Guide the team in the technical execution of the project, ensuring the approach is scalable and aligned with the overall objectives.
• Ensure the generated results meet accuracy benchmarks, as measured against the gold standard.
• Collaborate with the team to continuously improve processes, based on feedback and performance metrics.
• Report on project status and results, providing actionable insights to both technical and non-technical stakeholders