AI Engineering Lead

We are seeking an AI Engineer to join the DPS Engineering team, embedded within a cross-functional product delivery squad. This role will focus on designing, building, and deploying AI-driven capabilities that enhance product features, improve operational efficiency, and support data-driven decision-making.

The individual will work closely with product managers, engineers, and domain experts to translate business requirements into scalable AI solutions, ensuring seamless integration into production systems.

1. AI Solution Development

• Design, develop, and deploy machine learning and AI models (e.g., NLP, predictive analytics, GenAI use cases) aligned with product objectives

• Translate business problems into AI/ML solutions with clear success metrics

1. Product Integration

• Embed AI capabilities into product features and workflows within the delivery squad

• Collaborate with backend/frontend engineers to ensure scalable and reliable deployment

1. Model Lifecycle Management

• Build and maintain end-to-end ML pipelines (data ingestion, training, evaluation, deployment, monitoring)

• Ensure continuous improvement through model retraining and performance tuning

1. Data & Engineering Collaboration

• Work with data engineers to define data requirements, pipelines, and data quality standards

• Ensure proper feature engineering and dataset governance

1. Risk, Governance & Responsible AI

• Ensure AI solutions comply with enterprise standards on security, privacy, and responsible AI usage

• Document models, assumptions, and limitations clearly

Requirements:

• Strong experience in Python and AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)

• Experience with GenAI / LLMs (e.g., prompt engineering, RAG architectures, API-based models)

• Familiarity with MLOps practices (CI/CD, model deployment, monitoring)

• Experience working with cloud platforms (Azure preferred, AWS/GCP acceptable)

• Knowledge of data engineering concepts (SQL, data pipelines, APIs)

• Proven track record of delivering AI solutions in production environments

• Experience working in agile, squad-based delivery models

• Strong problem-solving mindset with a focus on business impact

• Ability to work in fast-paced, iterative delivery environments

• Effective collaboration across engineering, product, and business teams

• Curiosity and drive to continuously learn emerging AI technologies