About ktsawe are ktsa – kpmg technology services americas.a service delivery center of kpmg us, with offices in mexico city, guadalajara, and a growing network of remote talent across the country.we deliver high-value technology, consulting, and corporate support services to kpmg us and its clients.explore isn't just a word — it's how we grow, lead, and thrive.excelby creating impact and leaving your mark on global projects.this role was created to instill structure and best practices into the local development process.the development manager is responsible for managing the team's execution, ensuring the delivery of high-quality ai solutions, and mentoring the technical talent within the ktsa center.lead and mentor the technical team: provide clear direction, guidance, and mentorship to the development pod, fostering a collaborative and inclusive environment and ensuring the quality of all technical deliverables meets team standards.oversee the development lifecycle: implement and manage an agile development process, overseeing the end-to-end lifecycle from technical design through to testing and deployment.ensure technical quality and adherence to standards: conduct code reviews and ensure the team delivers high-quality, scalable code that aligns with the established architectural framework.partner for execution: collaborate closely with the ktsa ai lead to translate project goals into actionable technical requirements and development sprints.track and report on team velocity, project status, technical risks, and timelines to the ktsa ai lead.ai development lifecycle:knowledge of the end-to-end software development lifecycle (sdlc) as it applies to building ai/ml solutions.this includes managing agile sprints, overseeing data preparation, guiding experimentation, and managing the model development, testing, and deployment phases.
(applying agile/scrum methodologies to an ml project, managing a backlog of ai features)) devops for ai (mlops):this includes building ci/cd pipelines for models, versioning for both data and code, and monitoring model performance in a production environment.
(implementing automated model retraining pipelines, using git for model version control)) this involves proficiency with scripting languages and using both low-code and pro-code tools to quickly test hypotheses and build minimum viable products (mvps) for new ai solutions.
(building a simple chatbot using a vendor api, creating automation scripts in python)) ai quality assurance:knowledge of the methods and frameworks for testing and validating ai and ml systems.this includes understanding model evaluation metrics, strategies for ensuring data quality, and techniques for identifying bias and performance degradation in models.
(establishing a process for a/b testing models, creating a test suite for data validation)) experience:minimum of five years of recent experience in a technical role, with at least two years spent managing or leading software development teams.technical management:strong understanding of the full sdlc, agile methodologies, and modern software engineering principles.strong problem-solving skills with the ability to react quickly to technical problems during complex project sprints.bachelor's degree in computer science, engineering, or a related technical field.hybrid work model learning opportunities, training, and certification programs comprehensive medical plan, life insurance, car insurance, and funeral assistance we are supportive of helping you to achieve a balance between your home and work demands.we are happy to discuss specific requirements and our range of flexible working arrangements could be of interest.ktsa - kpmg technology services of americas