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 DevelopmentDesign, develop, and deploy machine learning and AI models (e.g., NLP, predictive analytics, GenAI use cases) aligned with product objectivesTranslate business problems into AI/ML solutions with clear success metrics2. Product IntegrationEmbed AI capabilities into product features and workflows within the delivery squadCollaborate with backend/frontend engineers to ensure scalable and reliable deployment3. Model Lifecycle ManagementBuild and maintain end-to-end ML pipelines (data ingestion, training, evaluation, deployment, monitoring)Ensure continuous improvement through model retraining and performance tuning4. Data & Engineering CollaborationWork with data engineers to define data requirements, pipelines, and data quality standardsEnsure proper feature engineering and dataset governance5. Risk, Governance & Responsible AIEnsure AI solutions comply with enterprise standards on security, privacy, and responsible AI usageDocument models, assumptions, and limitations clearlyRequirements: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 environmentsExperience working in agile, squad-based delivery modelsStrong problem-solving mindset with a focus on business impactAbility to work in fast-paced, iterative delivery environmentsEffective collaboration across engineering, product, and business teamsCuriosity and drive to continuously learn emerging AI technologies